Chi square is used with nominal data, determine whether or not a significant difference exists between the observed number and expected number of cases falling into each category.
True/ False
Solution:
True.
In chi-square goodness of fit test , we test the hypothesis if observed frequencies are same as expected frequencies or not for any type of variable like nominal or ordinal or ratio.
For example, For testing colors of M&M's chocolates are equally distributed in each pack , we use Chi-square goodness of fit test.
Here colors of M&M's chocolates are just nominal or have just names.
Thus given statement is True.
Chi square is used with nominal data, determine whether or not a significant difference exists between...
Chi-Square Test for Independence Using Chi-Square, we are looking to see if there is a significant difference between what we would expect results to be, and what the actual results were. That is, expected vs. observed. Use alpha = .05 Listed below are data from a survey conducted recently where Males and Females responded to their happiness with their supervisor (this is fictitious data). Response Male Female Total Not at all 23 25 48 Somewhat 13 22 35 Very 26 16 42...
When Chi-square distribution is used as a test of independence, the number of degrees of freedom is related to both the number of rows and the number of columns in the contingency table. Select one: True False Question 2 Answer saved Points out of 1.000 Flag question Question text A goodness of fit test can be used to determine if membership in categories of one variable is different as a function of membership in the categories of a second variable...
Why will the chi square value be large when the difference between observed and expected is large?
Explain the difference between observed frequency and expected frequency as it relates to Chi-Square test.
2 PLS Assumptions for the chi-square goodness-of-fit test are 1) the data are obtained from a random sample; and 2) the expected frequency for each category must be 5 or more. O True False
-If the value of chi-square is large and cannot be accounted for based on sampling error, the researcher should: fail to reject the null hypothesis reject the null hypothesis determine the degrees of freedom in the study observe the chi-square in the common zone. -If %Expected = 19 and N = 33, what is the value of fExpected? 6.08 0.63 6.27 5.7 -A psychology professor is studying whether a significant difference exists in the majors among students in her general...
Please help me answer #3. The chi^2 value means nothing on its own-it is used to find the probability that, assuming the hypothesis is true, the observed data set could have resulted from random fluctuations. A low probability suggests that the observed data are not consistent with the hypothesis, and thus the hypothesis should be rejected. A standard cutoff point used by biologists is a probability of 0.05 (5%). If the probability corresponding to the chi^2 value is 0.05 or...
A chi-square test of independence was used to determine whether race and medical aid (like insurance) were associated in a study of South African babies. Using the output shown below determine the most appropriate interpretation from among the choices given: Race Medical MedicaBlack White Total aid 27 114 (220.1) (20.9) 241 Yes 1325 24 (1231.9) (117.1) 1349 No Total 14521381590 Pearson Chi-Square 534.64, DF-1, P-Value 0.000 Select one: O a. There is an association between race and medical aid. White...
A chi-square test of independence was used to determine whether race and medical aid (like insurance) were associated in a study of South African babies. Using the output shown below determine the most appropriate interpretation from among the choices given: Race Medical aid Black White Total Yes 127 (220.1) 114 (20.9) 241 No 1325 (1231.9) 24 (117.1) 1349 Total 1452 138 1590 Pearson Chi-Square = 534.64, DF = 1, P-Value = 0.000 Select one: a. None of these choices. b....
In a chi-square test, what would it mean if the P-value were less than 5%? a. That there is no real difference between observed and expected values. b. That there is a difference between observed and expected values. c. That any difference between observed and expected values is probably not due to random chance. d. a and c are true e. b and c are true