Study groups are equivalent means that they areexactly the same number of male and female participants in each groupstatistically the same because sampling error is eliminatedexperimentally the samestatistically equal, with small differences between groups due to samplingerror

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MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Earlier this semester, we learned to use 2-Sample-TTest to compare the population means of two independent populations. One-way ANOVA is more powerful because it could compare the population means of three or more independent populations. However, use of one-way ANOVA also requires the assumption that the populations have the same variance. In this exercise, we will compare and contrast One-way ANOVA and 2-Sample-TTest. With the 2-Sample- TTEST, we will first choose 'No' for the pooled variances option, then re-run the test while choosing 'Yes' for the pooled variances option. Use the following data to complete these tasks. Depending on if you choose to do this by hand or using code, use the data format that suits you best - LONG form on top or WIDE form on bottom. Treatment One One One One One One One One Two Two Two Two Two Two Two Two Treatment Treatment One Two 5.6 4.7 3.6 3.9 5.2 4.3 4.1 4.8 Response 5.6 4.7 3.6 3.9 5.2 4.3 4.1 4.8 3.4 2.3 4.4 3.5 3.7 5.8 2.8 4.7 p-value= 3.4 2.3…
One sample has n=7 and SS=35 and a second sample has n =17 and SS =45. What is the pooled variance for these two samples?
Two separate samples, each with n = 14 individuals, receive different treatments. After treatment, the first sample has SS = 1316 and the second has SS = 1620. Find the pooled Variance for two independent samples. (hundredths place) Type only the pooled variance.
Students in one class are asked to complete the same questionnaire 3 times throughout the semester: at the beginning, at the midterm, and at the end. The purpose of the questionnaire is to track students' perception of their progress at different points in the semester. Scores at Time 1 (beginning of the semester), Time 2 (midterm), and Time 3 (end of semester) are compared against one another. What type of analysis of variance would be appropriate for examining the results from this dataset?
If samples of a fixed size N are drawn randomly and with replacement from the same population of scores, should we expect the sample means to differ across samples? why or why not?
Let's use SPSS to run a one-sample t-test! Imagine that you are interested in whether the number of hours students in a statistics course work each week differs from the average number of hours reported by the general student body at ASU. Thankfully, you have a data set that consists of information from students in a statistics course, including how many hours they work each week ("workhours"). You also happen to know that the average number of hours worked each week by the general student population at ASU is 25. Use the data provided to conduct a one sample t-test in SPSS comparing the sample data to the population mean.. The dependent variable for your test should be "workhours". Based on your output, the average number of hours worked each week by a sample is ________ . Enter your answer rounded to two decimal places (i.e., 10.01, not 10.1, not 10.0, not 10.010).
Earlier this semester, we learned to use 2-Sample-TTest to compare the population means of two independent populations. One-way ANOVA is more powerful because it could compare the population means of three or more independent populations. However, use of one-way ANOVA also requires the assumption that the populations have the same variance. In this exercise, we will compare and contrast One-way ANOVA and 2-Sample-TTest. With the 2-Sample- TTEST, we will first choose 'No' for the pooled variances option, then re-run the test while choosing 'Yes' for the pooled variances option. Use the following data to complete these tasks. Depending on if you choose to do this by hand or using code, use the data format that suits you best - LONG form on top or WIDE form on bottom. Treatment One One One One One One One Two Two Two Two Two Two Two Treatment One 7.1 8.5 7.6 7.7 6.9 8.5 7.8 Response 7.1 8.5 7.6 7.7 6.9 8.5 7.8 1.4 4.1 4.3 3.9 4 4 4.6 p-value= Treatment Two 1.4 4.1 4.3 3.9 4 4 4.6 1. Use…
Explain the circumstances under which we would need to pool the variance for an independent samples t-test
A study aims to compare the social media usage rates of men and women. Nine men and 9 women are drawn from the general population and the average time (in minutes) they spent on social media each day was compared (men’s mean = 40, sum of squares = 153; women’s mean = 48, sum of squares = 216). What is the (a) estimated population variance for each random sample, and (b) pooled variance? Estimated population variances = 19.13 and 27.00; Pooled variance = 23.07 Estimated population variances = 19.13 and 27.00; Pooled variance = 20.50 Estimated population variances = 17.00 and 24.00; Pooled variance = 20.50 Estimated population variances = 17.00 and 24.00; Pooled variance = 23.07
Describe a study in which you can use both nonparametric and parametric statistics. A researcher has participants expecting to receive either painful or mild electrical shocks during a study wait in a quarter-full waiting room with other participants. He then measures whether they choose to sit next to other participants or if they sit far away on their own. What is the best test to run for this study and why?
Two separate samples, each with n = 14 individuals, receive different treatments. After treatment, the first sample has SS = 1512 and the second has SS = 1620. Find the pooled Variance for two independent samples. (hundredths place) Type only the pooled variance.
If the underlying population of study is not normally distributed, how large should the sample size be? What if the population is normally distributed ?

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Study groups are equivalent means that they are exactly the same number of male and female participants in each group statistically the same because sampling error is eliminated experimentally the same statistically equal, with small differences between groups due to sampling error