Answer:
1. Chi-square for goodness of fit.
2. Two-sample proportion test
3. One-sample hypothesis test for mean
4. One-sample proportion test
5. Two-sample hypothesis test for mean
Step-by-step explanation:
The statistical procedures suitable for each of these scenarios.
1) Chi-square for goodness of fit
In Chi-Square goodness of fit test, the term goodness of fit is used to compare the observed sample distribution with the expected probability distribution. Chi-Square goodness of fit test determines how well theoretical distribution fits the empirical distribution. In Mr Taylor's class' observation, the expected sample distribution is even distribution, by counting and sorting, they want to determine the theoretical distribution. Therefore Chi-square for goodness of fit is suitable.
2) Two - sample proportion test
Two sample proportion test is used to determine whether the proportions of two groups differ. It calculates the range of values that is likely to include the difference between the population proportions. Since there are two groups and we want to determine the proportion at which they differ, two-sample proportion test is suitable.
3) One - sample hypothesis test for mean
The One Sample Test is commonly used to test the Statistical difference between a sample mean and a known value of the mean in the population.
4) One-sample proportion test
The One-Sample Proportion Test is used to assess whether a population proportion is significantly different from a hypothesized value. The only population here is the population of Americans claiming to limit their consumption of sweeteners.
5) Two-sample hypothesis test for mean
The two-sample hypothesis test is used to determine if two population means are equal. The two populations here are the undergraduate students from the statistics department and the math department.
