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My Post: Use for comparison
The Chi-sq integrity of-fit test measures whether the watched information is supporting the guaranteed populace or not. It tests for the noteworthy contrast between the asserted populace and watched information so see whether we can reason that the example information is essentially unique in relation to the guaranteed populace. It is altogether unique in relation to the t-test and the chi-square test of freedom. The autonomous t-test tests for the mean between two populaces and the chi-square test of autonomy tests for the freedom between two clear cut variable and subsequently the chi-square decency of-fit test is entirely unexpected from the above two. We realize that we need to utilize chi-square decency of-fit test when we have given some data about the populace and we need to test whether the information backings are it or not. Take into consideration the following real world situation:
A specialist arranges a study in which a pivotal stride is putting forth members a sustenance reward. It is critical that the three nourishment prizes be equivalent in offer. Consequently, a pre-study was outlined in which members were solicited from which prizes they favored. Of the 60 members, 16 favored cupcakes, 26 favored pieces of candy, and 18 favored dried apricots. Do these scores propose that the diverse nourishment are deferentially favored by individuals all in all? For this situation we need to test whether the extent of favored sustenance for various individuals are equivalent or not consequently a chi-square integrity of-fit test would be generally suitable.
Question 1 - Chantinique
What is another real life example that would be suitable to test?
Respond to student:
Question 2 - Najette
Of the 60 members, 16 favored cupcakes, 26 favored pieces of candy, and 18 favored dried apricots. Do these scores propose that the diverse nourishment are deferentially favored by individuals all in all?
Conduct an ANOVA comparing anxiety levels (at post test only) of participants across all three treatments, conduct post hoc test if needed.
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Develop a probability distribution for the number of students in the sample who watch soap operas.
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