MAT

4a79_0001

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

alternative hypothesis, H_a for this hypothesis, the expected values may be impossible to calculate chi-square (χ²) test statistic if this value is large, then there is stronger evidence in against of the null hypothesis, H₀ p-value if this value is small, it suggests that the observed data are NOT consistent with the null hypothesis, H₀ degrees of freedom in a chi-square (χ²) test, it is usually the number of categories minus one MAT

4a79_04ae

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

alternative hypothesis, H_a for this hypothesis, the expected values may be impossible to calculate p-value if this value is small, then there is stronger evidence in against of the null hypothesis, H₀ null hypothesis, H₀ we want to reject this hypothesis in our chi-square (χ²) test level of significance, α a fixed probability cutoff whether the null hypothesis, H₀ is assumed to be accepted or rejected MAT

4a79_04bb

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

p-value represents the probability of occurrence of the given observations chi-square (χ²) test statistic if this value is large, then there is stronger evidence in against of the null hypothesis, H₀ degrees of freedom this value determines which row of the chi-square (χ²) critical value table you should use null hypothesis, H₀ we want to reject this hypothesis in our chi-square (χ²) test MAT

4a79_0682

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

alternative hypothesis, H_a we want to accept this hypothesis in our chi-square (χ²) test chi-square (χ²) test statistic if this value is large, then there is stronger evidence in against of the null hypothesis, H₀ p-value the probability of getting a result that is either the same or more extreme than the actual observations level of significance, α biologists use a probability of 0.05 (5%) for this value MAT

4a79_071a

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

degrees of freedom represents how many independent values can vary in the calculation after constraints are applie alternative hypothesis, H_a we want to accept this hypothesis in our chi-square (χ²) test chi-square (χ²) test statistic the bigger this number, the smaller the p-value null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values MAT

4a79_0f28

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

chi-square (χ²) test statistic if this value is large, then there is stronger evidence in favor of the alternative hypothesis, H_a critical value the boundary of how extreme a test statistic we need to reject the null hypothesis, H₀ null hypothesis, H₀ we want to reject this hypothesis in our chi-square (χ²) test alternative hypothesis, H_a if the null hypothesis, H₀ is disproved, then this opposing hypothesis gets accepted MAT

4a79_0f72

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

chi-square (χ²) test statistic the bigger this number, the smaller the p-value null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test level of significance, α a fixed probability cutoff whether the null hypothesis, H₀ is assumed to be accepted or rejected p-value if this value is small, then there is stronger evidence in favor of the alternative hypothesis, H_a MAT

4a79_15ff

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

critical value the sum of the normalized square difference between observed and expected data level of significance, α a constant probability that provides a cutoff for falsification of the null hypothesis, H₀ null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values chi-square (χ²) test statistic if this value is large, then there is stronger evidence in favor of the alternative hypothesis, H_a MAT

4a79_16fe

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

p-value represents the probability of occurrence of the given observations null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test critical value a measure of the discrepancy between the observed and expected data sets chi-square (χ²) test statistic if this value is large, then there is stronger evidence in favor of the alternative hypothesis, H_a MAT

4a79_17b3

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

null hypothesis, H₀ we want to reject this hypothesis in our chi-square (χ²) test degrees of freedom represents how many independent values can vary in the calculation after constraints are applie alternative hypothesis, H_a if the null hypothesis, H₀ is disproved, then this opposing hypothesis gets accepted critical value a measure of the discrepancy between the observed and expected data sets MAT

4a79_1916

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

critical value a measure of the discrepancy between the observed and expected data sets degrees of freedom this value determines which row of the chi-square (χ²) critical value table you should use alternative hypothesis, H_a we are attempting to demonstrate this hypothesis in an indirect way by using the chi-square (χ²) test null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values MAT

4a79_19f1

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

p-value represents the probability of occurrence of the given observations alternative hypothesis, H_a if the null hypothesis, H₀ is disproved, then this opposing hypothesis gets accepted chi-square (χ²) test statistic if this value is large, then there is stronger evidence in against of the null hypothesis, H₀ level of significance, α a constant probability that provides a cutoff for falsification of the null hypothesis, H₀ MAT

4a79_1b73

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

degrees of freedom represents how many independent values can vary in the calculation after constraints are applie p-value if this value is small, it suggests that the observed data are NOT consistent with the null hypothesis, H₀ null hypothesis, H₀ we want to reject this hypothesis in our chi-square (χ²) test critical value the sum of the normalized square difference between observed and expected data MAT

4a79_1c1c

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

level of significance, α the cutoff of how small a p-value we need to reject the null hypothesis, H₀ chi-square (χ²) test statistic the bigger this number, the smaller the p-value critical value a measure of the discrepancy between the observed and expected data sets alternative hypothesis, H_a if the null hypothesis, H₀ is disproved, then this opposing hypothesis gets accepted MAT

4a79_1c6b

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

chi-square (χ²) test statistic if this value is large, then there is stronger evidence in against of the null hypothesis, H₀ p-value if this value is small, then there is stronger evidence in against of the null hypothesis, H₀ critical value the sum of the normalized square difference between observed and expected data null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values MAT

4a79_1dc6

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

null hypothesis, H₀ we want to reject this hypothesis in our chi-square (χ²) test critical value found in a table for a given degrees of freedom and level of significance, α degrees of freedom most often this number is one less than the number of observations (rows in our table) p-value if this value is small, then there is stronger evidence in against of the null hypothesis, H₀ MAT

4a79_2290

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test critical value the cutoff used to compare against the observed chi-square (χ²) test statistic alternative hypothesis, H_a we want to accept this hypothesis in our chi-square (χ²) test level of significance, α biologists use a probability of 0.05 (5%) for this value MAT

4a79_2b1a

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

critical value found in a table for a given degrees of freedom and level of significance, α null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test level of significance, α biologists use a probability of 0.05 (5%) for this value p-value the probability of getting a result that is either the same or more extreme than the actual observations MAT

4a79_35be

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

degrees of freedom in a chi-square (χ²) test, it is usually the number of categories minus one alternative hypothesis, H_a we want to accept this hypothesis in our chi-square (χ²) test chi-square (χ²) test statistic the bigger this number, the smaller the p-value p-value the probability of getting a result that is either the same or more extreme than the actual observations MAT

4a79_36d8

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

alternative hypothesis, H_a we want to accept this hypothesis in our chi-square (χ²) test level of significance, α standard cutoff probability used to determine statistic significance critical value the sum of the normalized square difference between observed and expected data p-value if this value is small, it suggests that the observed data are NOT consistent with the null hypothesis, H₀ MAT

4a79_38b9

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

alternative hypothesis, H_a if the null hypothesis, H₀ is disproved, then this opposing hypothesis gets accepted degrees of freedom represents how many independent values can vary in the calculation after constraints are applie chi-square (χ²) test statistic the bigger this number, the smaller the p-value p-value represents the probability of occurrence of the given observations MAT

4a79_38d5

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

degrees of freedom this value determines which row of the chi-square (χ²) critical value table you should use alternative hypothesis, H_a we are attempting to demonstrate this hypothesis in an indirect way by using the chi-square (χ²) test null hypothesis, H₀ we want to reject this hypothesis in our chi-square (χ²) test chi-square (χ²) test statistic if this value is large, then there is stronger evidence in favor of the alternative hypothesis, H_a MAT

4a79_3c89

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

level of significance, α the statistical cutoff of the result for the null hypothesis, H₀ to be TRUE or false null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values degrees of freedom this value determines which row of the chi-square (χ²) critical value table you should use p-value the smaller this number, the bigger the chi-square (χ²) test statistic MAT

4a79_3d07

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

critical value the boundary of how extreme a test statistic we need to reject the null hypothesis, H₀ null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values alternative hypothesis, H_a for this hypothesis, the expected values may be impossible to calculate chi-square (χ²) test statistic the bigger this number, the smaller the p-value MAT

4a79_3e98

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

degrees of freedom this value determines which row of the chi-square (χ²) critical value table you should use critical value the boundary of how extreme a test statistic we need to reject the null hypothesis, H₀ p-value the probability of getting a result that is either the same or more extreme than the actual observations alternative hypothesis, H_a we are attempting to demonstrate this hypothesis in an indirect way by using the chi-square (χ²) test MAT

4a79_3ec8

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

p-value represents the probability of occurrence of the given observations null hypothesis, H₀ we want to reject this hypothesis in our chi-square (χ²) test critical value found in a table for a given degrees of freedom and level of significance, α alternative hypothesis, H_a for this hypothesis, the expected values may be impossible to calculate MAT

4a79_3ee8

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

critical value found in a table for a given degrees of freedom and level of significance, α p-value if this value is small, then there is stronger evidence in favor of the alternative hypothesis, H_a degrees of freedom represents how many independent values can vary in the calculation after constraints are applie chi-square (χ²) test statistic if this value is large, then there is stronger evidence in favor of the alternative hypothesis, H_a MAT

4a79_457a

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

critical value found in a table for a given degrees of freedom and level of significance, α alternative hypothesis, H_a for this hypothesis, the expected values may be impossible to calculate p-value the smaller this number, the bigger the chi-square (χ²) test statistic null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values MAT

4a79_4613

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

p-value if this value is small, then there is stronger evidence in against of the null hypothesis, H₀ level of significance, α the cutoff of how small a p-value we need to reject the null hypothesis, H₀ chi-square (χ²) test statistic the bigger this number, the smaller the p-value null hypothesis, H₀ we want to reject this hypothesis in our chi-square (χ²) test MAT

4a79_47d6

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

critical value the cutoff used to compare against the observed chi-square (χ²) test statistic level of significance, α the fixed probability for elimination of null hypothesis, H₀ chi-square (χ²) test statistic if this value is large, then there is stronger evidence in favor of the alternative hypothesis, H_a alternative hypothesis, H_a if the null hypothesis, H₀ is disproved, then this opposing hypothesis gets accepted MAT

4a79_4a33

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

chi-square (χ²) test statistic the bigger this number, the smaller the p-value alternative hypothesis, H_a we want to accept this hypothesis in our chi-square (χ²) test level of significance, α the cutoff of how small a p-value we need to reject the null hypothesis, H₀ null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values MAT

4a79_4ebd

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

degrees of freedom in a chi-square (χ²) test, it is usually the number of categories minus one alternative hypothesis, H_a for this hypothesis, the expected values may be impossible to calculate critical value a measure of the discrepancy between the observed and expected data sets null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values MAT

4a79_4ec3

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

critical value the cutoff used to compare against the observed chi-square (χ²) test statistic level of significance, α the statistical cutoff of the result for the null hypothesis, H₀ to be TRUE or false degrees of freedom in a chi-square (χ²) test, it is usually the number of categories minus one null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test MAT

4a79_50a7

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

degrees of freedom in a chi-square (χ²) test, it is usually the number of categories minus one alternative hypothesis, H_a for this hypothesis, the expected values may be impossible to calculate p-value if this value is small, then there is stronger evidence in favor of the alternative hypothesis, H_a level of significance, α standard cutoff probability used to determine statistic significance MAT

4a79_54db

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

degrees of freedom represents how many independent values can vary in the calculation after constraints are applie level of significance, α biologists use a probability of 0.05 (5%) for this value chi-square (χ²) test statistic if this value is large, then there is stronger evidence in against of the null hypothesis, H₀ critical value found in a table for a given degrees of freedom and level of significance, α MAT

4a79_5515

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

degrees of freedom represents how many independent values can vary in the calculation after constraints are applie p-value represents the probability of occurrence of the given observations alternative hypothesis, H_a if the null hypothesis, H₀ is disproved, then this opposing hypothesis gets accepted level of significance, α the fixed probability for elimination of null hypothesis, H₀ MAT

4a79_5609

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

critical value the cutoff used to compare against the observed chi-square (χ²) test statistic degrees of freedom represents how many independent values can vary in the calculation after constraints are applie null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values chi-square (χ²) test statistic the bigger this number, the smaller the p-value MAT

4a79_5bee

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

critical value the cutoff used to compare against the observed chi-square (χ²) test statistic null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values alternative hypothesis, H_a for this hypothesis, the expected values may be impossible to calculate degrees of freedom this value determines which row of the chi-square (χ²) critical value table you should use MAT

4a79_5cb5

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

p-value if this value is small, it suggests that the observed data are NOT consistent with the null hypothesis, H₀ chi-square (χ²) test statistic if this value is large, then there is stronger evidence in against of the null hypothesis, H₀ degrees of freedom represents how many independent values can vary in the calculation after constraints are applie critical value found in a table for a given degrees of freedom and level of significance, α MAT

4a79_5e0b

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

critical value the boundary of how extreme a test statistic we need to reject the null hypothesis, H₀ null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values degrees of freedom most often this number is one less than the number of observations (rows in our table) alternative hypothesis, H_a we are attempting to demonstrate this hypothesis in an indirect way by using the chi-square (χ²) test MAT

4a79_6301

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

level of significance, α a fixed probability cutoff whether the null hypothesis, H₀ is assumed to be accepted or rejected degrees of freedom represents how many independent values can vary in the calculation after constraints are applie alternative hypothesis, H_a for this hypothesis, the expected values may be impossible to calculate p-value the probability of getting a result that is either the same or more extreme than the actual observations MAT

4a79_6482

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

level of significance, α the cutoff of how small a p-value we need to reject the null hypothesis, H₀ null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values alternative hypothesis, H_a for this hypothesis, the expected values may be impossible to calculate critical value found in a table for a given degrees of freedom and level of significance, α MAT

4a79_6666

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

degrees of freedom most often this number is one less than the number of observations (rows in our table) p-value represents the probability of occurrence of the given observations null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values critical value the cutoff used to compare against the observed chi-square (χ²) test statistic MAT

4a79_6f88

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

chi-square (χ²) test statistic if this value is large, then there is stronger evidence in favor of the alternative hypothesis, H_a p-value if this value is small, it suggests that the observed data are NOT consistent with the null hypothesis, H₀ alternative hypothesis, H_a we want to accept this hypothesis in our chi-square (χ²) test null hypothesis, H₀ we want to reject this hypothesis in our chi-square (χ²) test MAT

4a79_723c

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

chi-square (χ²) test statistic the bigger this number, the smaller the p-value critical value a measure of the discrepancy between the observed and expected data sets alternative hypothesis, H_a we want to accept this hypothesis in our chi-square (χ²) test null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test MAT

4a79_76c9

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

degrees of freedom most often this number is one less than the number of observations (rows in our table) critical value the cutoff used to compare against the observed chi-square (χ²) test statistic chi-square (χ²) test statistic the bigger this number, the smaller the p-value level of significance, α a fixed probability cutoff whether the null hypothesis, H₀ is assumed to be accepted or rejected MAT

4a79_77fd

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

level of significance, α a fixed probability cutoff whether the null hypothesis, H₀ is assumed to be accepted or rejected degrees of freedom this value determines which row of the chi-square (χ²) critical value table you should use alternative hypothesis, H_a we are attempting to demonstrate this hypothesis in an indirect way by using the chi-square (χ²) test chi-square (χ²) test statistic if this value is large, then there is stronger evidence in favor of the alternative hypothesis, H_a MAT

4a79_79b3

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

degrees of freedom this value determines which row of the chi-square (χ²) critical value table you should use alternative hypothesis, H_a we want to accept this hypothesis in our chi-square (χ²) test p-value if this value is small, then there is stronger evidence in favor of the alternative hypothesis, H_a chi-square (χ²) test statistic if this value is large, then there is stronger evidence in favor of the alternative hypothesis, H_a MAT

4a79_7d17

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

critical value the cutoff used to compare against the observed chi-square (χ²) test statistic p-value represents the probability of occurrence of the given observations chi-square (χ²) test statistic if this value is large, then there is stronger evidence in against of the null hypothesis, H₀ alternative hypothesis, H_a we want to accept this hypothesis in our chi-square (χ²) test MAT

4a79_7e58

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

p-value if this value is small, then there is stronger evidence in against of the null hypothesis, H₀ null hypothesis, H₀ we want to reject this hypothesis in our chi-square (χ²) test critical value found in a table for a given degrees of freedom and level of significance, α degrees of freedom represents how many independent values can vary in the calculation after constraints are applie MAT

4a79_8079

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

level of significance, α a constant probability that provides a cutoff for falsification of the null hypothesis, H₀ degrees of freedom this value determines which row of the chi-square (χ²) critical value table you should use chi-square (χ²) test statistic the bigger this number, the smaller the p-value alternative hypothesis, H_a if the null hypothesis, H₀ is disproved, then this opposing hypothesis gets accepted MAT

4a79_857b

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

chi-square (χ²) test statistic if this value is large, then there is stronger evidence in against of the null hypothesis, H₀ alternative hypothesis, H_a we want to accept this hypothesis in our chi-square (χ²) test p-value if this value is small, then there is stronger evidence in favor of the alternative hypothesis, H_a null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values MAT

4a79_8643

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

level of significance, α the statistical cutoff of the result for the null hypothesis, H₀ to be TRUE or false alternative hypothesis, H_a we are attempting to demonstrate this hypothesis in an indirect way by using the chi-square (χ²) test p-value represents the probability of occurrence of the given observations degrees of freedom this value determines which row of the chi-square (χ²) critical value table you should use MAT

4a79_8658

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

p-value if this value is small, it suggests that the observed data are NOT consistent with the null hypothesis, H₀ level of significance, α a constant probability that provides a cutoff for falsification of the null hypothesis, H₀ degrees of freedom most often this number is one less than the number of observations (rows in our table) alternative hypothesis, H_a for this hypothesis, the expected values may be impossible to calculate MAT

4a79_933d

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

level of significance, α a fixed probability cutoff whether the null hypothesis, H₀ is assumed to be accepted or rejected alternative hypothesis, H_a for this hypothesis, the expected values may be impossible to calculate p-value the smaller this number, the bigger the chi-square (χ²) test statistic degrees of freedom this value determines which row of the chi-square (χ²) critical value table you should use MAT

4a79_9514

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

critical value the cutoff used to compare against the observed chi-square (χ²) test statistic alternative hypothesis, H_a we are attempting to demonstrate this hypothesis in an indirect way by using the chi-square (χ²) test p-value represents the probability of occurrence of the given observations level of significance, α the cutoff of how small a p-value we need to reject the null hypothesis, H₀ MAT

4a79_9604

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

alternative hypothesis, H_a for this hypothesis, the expected values may be impossible to calculate critical value the cutoff used to compare against the observed chi-square (χ²) test statistic null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values chi-square (χ²) test statistic if this value is large, then there is stronger evidence in favor of the alternative hypothesis, H_a MAT

4a79_9627

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

level of significance, α the statistical cutoff of the result for the null hypothesis, H₀ to be TRUE or false degrees of freedom represents how many independent values can vary in the calculation after constraints are applie p-value represents the probability of occurrence of the given observations alternative hypothesis, H_a for this hypothesis, the expected values may be impossible to calculate MAT

4a79_9804

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

degrees of freedom this value determines which row of the chi-square (χ²) critical value table you should use critical value the sum of the normalized square difference between observed and expected data null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test p-value represents the probability of occurrence of the given observations MAT

4a79_9aba

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

chi-square (χ²) test statistic if this value is large, then there is stronger evidence in against of the null hypothesis, H₀ alternative hypothesis, H_a if the null hypothesis, H₀ is disproved, then this opposing hypothesis gets accepted p-value if this value is small, it suggests that the observed data are NOT consistent with the null hypothesis, H₀ critical value the sum of the normalized square difference between observed and expected data MAT

4a79_9b81

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

alternative hypothesis, H_a for this hypothesis, the expected values may be impossible to calculate null hypothesis, H₀ we want to reject this hypothesis in our chi-square (χ²) test chi-square (χ²) test statistic if this value is large, then there is stronger evidence in against of the null hypothesis, H₀ critical value the cutoff used to compare against the observed chi-square (χ²) test statistic MAT

4a79_a95a

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

chi-square (χ²) test statistic if this value is large, then there is stronger evidence in favor of the alternative hypothesis, H_a alternative hypothesis, H_a if the null hypothesis, H₀ is disproved, then this opposing hypothesis gets accepted p-value represents the probability of occurrence of the given observations level of significance, α the fixed probability for elimination of null hypothesis, H₀ MAT

4a79_a983

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

null hypothesis, H₀ we want to reject this hypothesis in our chi-square (χ²) test alternative hypothesis, H_a we want to accept this hypothesis in our chi-square (χ²) test p-value if this value is small, it suggests that the observed data are NOT consistent with the null hypothesis, H₀ chi-square (χ²) test statistic the bigger this number, the smaller the p-value MAT

4a79_aa80

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test chi-square (χ²) test statistic the bigger this number, the smaller the p-value degrees of freedom in a chi-square (χ²) test, it is usually the number of categories minus one p-value the probability of getting a result that is either the same or more extreme than the actual observations MAT

4a79_ad34

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

null hypothesis, H₀ we want to reject this hypothesis in our chi-square (χ²) test alternative hypothesis, H_a for this hypothesis, the expected values may be impossible to calculate chi-square (χ²) test statistic if this value is large, then there is stronger evidence in favor of the alternative hypothesis, H_a critical value the cutoff used to compare against the observed chi-square (χ²) test statistic MAT

4a79_ade8

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

critical value found in a table for a given degrees of freedom and level of significance, α null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test p-value the smaller this number, the bigger the chi-square (χ²) test statistic degrees of freedom most often this number is one less than the number of observations (rows in our table) MAT

4a79_b210

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

level of significance, α a fixed probability cutoff whether the null hypothesis, H₀ is assumed to be accepted or rejected null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values alternative hypothesis, H_a we are attempting to demonstrate this hypothesis in an indirect way by using the chi-square (χ²) test degrees of freedom most often this number is one less than the number of observations (rows in our table) MAT

4a79_b24e

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

p-value the probability of getting a result that is either the same or more extreme than the actual observations null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test critical value found in a table for a given degrees of freedom and level of significance, α degrees of freedom this value determines which row of the chi-square (χ²) critical value table you should use MAT

4a79_b7f0

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

chi-square (χ²) test statistic if this value is large, then there is stronger evidence in favor of the alternative hypothesis, H_a alternative hypothesis, H_a if the null hypothesis, H₀ is disproved, then this opposing hypothesis gets accepted null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test degrees of freedom most often this number is one less than the number of observations (rows in our table) MAT

4a79_baab

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

degrees of freedom in a chi-square (χ²) test, it is usually the number of categories minus one level of significance, α a constant probability that provides a cutoff for falsification of the null hypothesis, H₀ chi-square (χ²) test statistic if this value is large, then there is stronger evidence in favor of the alternative hypothesis, H_a critical value the boundary of how extreme a test statistic we need to reject the null hypothesis, H₀ MAT

4a79_baf2

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

p-value represents the probability of occurrence of the given observations degrees of freedom represents how many independent values can vary in the calculation after constraints are applie critical value a measure of the discrepancy between the observed and expected data sets alternative hypothesis, H_a we want to accept this hypothesis in our chi-square (χ²) test MAT

4a79_bb4f

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

critical value the cutoff used to compare against the observed chi-square (χ²) test statistic p-value if this value is small, then there is stronger evidence in favor of the alternative hypothesis, H_a level of significance, α the statistical cutoff of the result for the null hypothesis, H₀ to be TRUE or false degrees of freedom this value determines which row of the chi-square (χ²) critical value table you should use MAT

4a79_bcde

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values critical value the sum of the normalized square difference between observed and expected data degrees of freedom this value determines which row of the chi-square (χ²) critical value table you should use chi-square (χ²) test statistic if this value is large, then there is stronger evidence in against of the null hypothesis, H₀ MAT

4a79_c362

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

level of significance, α a fixed probability cutoff whether the null hypothesis, H₀ is assumed to be accepted or rejected p-value represents the probability of occurrence of the given observations alternative hypothesis, H_a for this hypothesis, the expected values may be impossible to calculate degrees of freedom represents how many independent values can vary in the calculation after constraints are applie MAT

4a79_c7ab

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

critical value a measure of the discrepancy between the observed and expected data sets degrees of freedom most often this number is one less than the number of observations (rows in our table) null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test p-value represents the probability of occurrence of the given observations MAT

4a79_ca37

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

level of significance, α a fixed probability cutoff whether the null hypothesis, H₀ is assumed to be accepted or rejected p-value if this value is small, then there is stronger evidence in favor of the alternative hypothesis, H_a critical value the cutoff used to compare against the observed chi-square (χ²) test statistic null hypothesis, H₀ we want to reject this hypothesis in our chi-square (χ²) test MAT

4a79_cfdd

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test p-value if this value is small, then there is stronger evidence in against of the null hypothesis, H₀ chi-square (χ²) test statistic if this value is large, then there is stronger evidence in against of the null hypothesis, H₀ alternative hypothesis, H_a if the null hypothesis, H₀ is disproved, then this opposing hypothesis gets accepted MAT

4a79_d0a0

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test p-value the probability of getting a result that is either the same or more extreme than the actual observations alternative hypothesis, H_a we want to accept this hypothesis in our chi-square (χ²) test chi-square (χ²) test statistic the bigger this number, the smaller the p-value MAT

4a79_d196

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

alternative hypothesis, H_a if the null hypothesis, H₀ is disproved, then this opposing hypothesis gets accepted degrees of freedom this value determines which row of the chi-square (χ²) critical value table you should use critical value a measure of the discrepancy between the observed and expected data sets level of significance, α biologists use a probability of 0.05 (5%) for this value MAT

4a79_d1ae

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

level of significance, α the fixed probability for elimination of null hypothesis, H₀ null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values alternative hypothesis, H_a if the null hypothesis, H₀ is disproved, then this opposing hypothesis gets accepted critical value the sum of the normalized square difference between observed and expected data MAT

4a79_d55b

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

degrees of freedom in a chi-square (χ²) test, it is usually the number of categories minus one p-value if this value is small, then there is stronger evidence in against of the null hypothesis, H₀ null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values critical value found in a table for a given degrees of freedom and level of significance, α MAT

4a79_d586

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

degrees of freedom this value determines which row of the chi-square (χ²) critical value table you should use alternative hypothesis, H_a we are attempting to demonstrate this hypothesis in an indirect way by using the chi-square (χ²) test critical value the boundary of how extreme a test statistic we need to reject the null hypothesis, H₀ p-value represents the probability of occurrence of the given observations MAT

4a79_d58b

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

alternative hypothesis, H_a if the null hypothesis, H₀ is disproved, then this opposing hypothesis gets accepted null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test chi-square (χ²) test statistic if this value is large, then there is stronger evidence in against of the null hypothesis, H₀ degrees of freedom most often this number is one less than the number of observations (rows in our table) MAT

4a79_d87f

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

critical value the cutoff used to compare against the observed chi-square (χ²) test statistic degrees of freedom this value determines which row of the chi-square (χ²) critical value table you should use level of significance, α the cutoff of how small a p-value we need to reject the null hypothesis, H₀ chi-square (χ²) test statistic the bigger this number, the smaller the p-value MAT

4a79_d9bd

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

level of significance, α a fixed probability cutoff whether the null hypothesis, H₀ is assumed to be accepted or rejected null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values p-value the smaller this number, the bigger the chi-square (χ²) test statistic critical value the sum of the normalized square difference between observed and expected data MAT

4a79_db66

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

critical value the cutoff used to compare against the observed chi-square (χ²) test statistic level of significance, α the statistical cutoff of the result for the null hypothesis, H₀ to be TRUE or false null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values alternative hypothesis, H_a for this hypothesis, the expected values may be impossible to calculate MAT

4a79_dfea

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

alternative hypothesis, H_a we want to accept this hypothesis in our chi-square (χ²) test critical value found in a table for a given degrees of freedom and level of significance, α degrees of freedom this value determines which row of the chi-square (χ²) critical value table you should use p-value the smaller this number, the bigger the chi-square (χ²) test statistic MAT

4a79_e484

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

critical value the boundary of how extreme a test statistic we need to reject the null hypothesis, H₀ p-value if this value is small, then there is stronger evidence in against of the null hypothesis, H₀ level of significance, α the cutoff of how small a p-value we need to reject the null hypothesis, H₀ degrees of freedom in a chi-square (χ²) test, it is usually the number of categories minus one MAT

4a79_e5b4

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

alternative hypothesis, H_a for this hypothesis, the expected values may be impossible to calculate p-value if this value is small, it suggests that the observed data are NOT consistent with the null hypothesis, H₀ null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values chi-square (χ²) test statistic if this value is large, then there is stronger evidence in favor of the alternative hypothesis, H_a MAT

4a79_e870

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

degrees of freedom represents how many independent values can vary in the calculation after constraints are applie null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test p-value represents the probability of occurrence of the given observations chi-square (χ²) test statistic if this value is large, then there is stronger evidence in against of the null hypothesis, H₀ MAT

4a79_e90f

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

p-value the smaller this number, the bigger the chi-square (χ²) test statistic null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values level of significance, α the cutoff of how small a p-value we need to reject the null hypothesis, H₀ chi-square (χ²) test statistic if this value is large, then there is stronger evidence in against of the null hypothesis, H₀ MAT

4a79_eb23

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

level of significance, α the fixed probability for elimination of null hypothesis, H₀ chi-square (χ²) test statistic if this value is large, then there is stronger evidence in against of the null hypothesis, H₀ p-value if this value is small, it suggests that the observed data are NOT consistent with the null hypothesis, H₀ degrees of freedom most often this number is one less than the number of observations (rows in our table) MAT

4a79_f02d

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

level of significance, α the cutoff of how small a p-value we need to reject the null hypothesis, H₀ degrees of freedom in a chi-square (χ²) test, it is usually the number of categories minus one null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values chi-square (χ²) test statistic if this value is large, then there is stronger evidence in favor of the alternative hypothesis, H_a MAT

4a79_f1d9

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test alternative hypothesis, H_a we are attempting to demonstrate this hypothesis in an indirect way by using the chi-square (χ²) test critical value the cutoff used to compare against the observed chi-square (χ²) test statistic degrees of freedom this value determines which row of the chi-square (χ²) critical value table you should use MAT

4a79_f32e

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

alternative hypothesis, H_a we want to accept this hypothesis in our chi-square (χ²) test degrees of freedom this value determines which row of the chi-square (χ²) critical value table you should use null hypothesis, H₀ we want to reject this hypothesis in our chi-square (χ²) test level of significance, α biologists use a probability of 0.05 (5%) for this value MAT

4a79_f4cb

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

chi-square (χ²) test statistic if this value is large, then there is stronger evidence in against of the null hypothesis, H₀ critical value a measure of the discrepancy between the observed and expected data sets null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values level of significance, α the statistical cutoff of the result for the null hypothesis, H₀ to be TRUE or false MAT

4a79_f523

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values degrees of freedom in a chi-square (χ²) test, it is usually the number of categories minus one level of significance, α the cutoff of how small a p-value we need to reject the null hypothesis, H₀ chi-square (χ²) test statistic if this value is large, then there is stronger evidence in against of the null hypothesis, H₀ MAT

4a79_f994

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

alternative hypothesis, H_a we are attempting to demonstrate this hypothesis in an indirect way by using the chi-square (χ²) test level of significance, α standard cutoff probability used to determine statistic significance null hypothesis, H₀ we want to reject this hypothesis in our chi-square (χ²) test degrees of freedom represents how many independent values can vary in the calculation after constraints are applie MAT

4a79_f9c6

Match each of the following chi-square (χ²) terms with their corresponding defintions.

Note: Each choice will be used exactly once.

degrees of freedom represents how many independent values can vary in the calculation after constraints are applie critical value the sum of the normalized square difference between observed and expected data p-value the probability of getting a result that is either the same or more extreme than the actual observations alternative hypothesis, H_a if the null hypothesis, H₀ is disproved, then this opposing hypothesis gets accepted