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Is there a significant difference in reported performance between the two groups of students? Use an independent-measures two-tailed test with a = .01. t-critical O Reject the null hypothesis; there is a significant difference. O Fail to reject the null hypothesis; there is no significant difference. O Reject the null hypothesis; there is no significant difference. O Fail to reject the null hypothesis; there is a significant difference.

Is there a significant difference in reported performance between the two groups of students? Use an independent-measures two-tailed test with a = .01. t-critical O Reject the null hypothesis; there is a significant difference. O Fail to reject the null hypothesis; there is no significant difference. O Reject the null hypothesis; there is no significant difference. O Fail to reject the null hypothesis; there is a significant difference.

MATLAB: An Introduction with Applications
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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**Chapter 10 End-of-Chapter Problems** **4. Gravetter/Wallnau/Forzano, - Chapter 10 - End-of-chapter question 7** Research results suggest a relationship between the TV viewing habits of 5-year-old children and their future performance in high school. For example, Anderson, Huston, Wright, and Collins (1998) report that high school students who regularly watched *Sesame Street* as children had better grades in high school than their peers who did not watch *Sesame Street*. Suppose that a researcher intends to examine this phenomenon using a sample of 20 high school students. The researcher first surveys the students’ parents to obtain information on the family’s TV viewing habits during the time that the students were 5 years old. Based on the survey results, the researcher selects a sample of n = 10 students with a history of watching *Sesame Street* and a sample of n = 10 students who did not watch the program. The average high school grade is recorded for each student, and the data are as follows: **Table: Average High School Grade** | Watched Sesame Street | Did Not Watch Sesame Street | |-----------------------|-----------------------------| | 86 | 79 | | 87 | 83 | | 91 | 86 | | 97 | 81 | | 98 | 92 | | **n = 10** | **n = 10** | | **M = 93** | **M = 85** | | **SS = 200** | **SS = 160** | - **M (Mean):** Represents the average score for each group. - **SS (Sum of Squares):** Indicates the total squared deviation from the mean. This data suggests a potential relationship between early childhood TV viewing habits and later academic performance.
Transcribed Image Text:**Chapter 10 End-of-Chapter Problems** **4. Gravetter/Wallnau/Forzano, - Chapter 10 - End-of-chapter question 7** Research results suggest a relationship between the TV viewing habits of 5-year-old children and their future performance in high school. For example, Anderson, Huston, Wright, and Collins (1998) report that high school students who regularly watched *Sesame Street* as children had better grades in high school than their peers who did not watch *Sesame Street*. Suppose that a researcher intends to examine this phenomenon using a sample of 20 high school students. The researcher first surveys the students’ parents to obtain information on the family’s TV viewing habits during the time that the students were 5 years old. Based on the survey results, the researcher selects a sample of n = 10 students with a history of watching *Sesame Street* and a sample of n = 10 students who did not watch the program. The average high school grade is recorded for each student, and the data are as follows: **Table: Average High School Grade** | Watched Sesame Street | Did Not Watch Sesame Street | |-----------------------|-----------------------------| | 86 | 79 | | 87 | 83 | | 91 | 86 | | 97 | 81 | | 98 | 92 | | **n = 10** | **n = 10** | | **M = 93** | **M = 85** | | **SS = 200** | **SS = 160** | - **M (Mean):** Represents the average score for each group. - **SS (Sum of Squares):** Indicates the total squared deviation from the mean. This data suggests a potential relationship between early childhood TV viewing habits and later academic performance.
## Chapter 10 End-of-Chapter Problems ### Question Is there a significant difference in reported performance between the two groups of students? Use an independent-measures two-tailed test with α = 0.01. ### Inputs Required - **t-critical = ±** [Input box with dropdown] - **t =** [Input box with dropdown] ### Options - ○ Reject the null hypothesis; there is a significant difference. - ○ Fail to reject the null hypothesis; there is no significant difference. - ○ Reject the null hypothesis; there is no significant difference. - ○ Fail to reject the null hypothesis; there is a significant difference. --- ### Diagram Explanation #### t Distribution Chart - **Graph Description:** The graph shows a symmetric bell-shaped curve representing the t distribution. - **Degrees of Freedom Slider:** Adjust the degrees of freedom for the distribution, currently set to 21. - **Graph Highlights:** - The curve is shaded, indicating the critical regions where the null hypothesis would be rejected. This interactive chart helps determine the critical t values based on the degrees of freedom, which are essential for hypothesis testing.
Transcribed Image Text:## Chapter 10 End-of-Chapter Problems ### Question Is there a significant difference in reported performance between the two groups of students? Use an independent-measures two-tailed test with α = 0.01. ### Inputs Required - **t-critical = ±** [Input box with dropdown] - **t =** [Input box with dropdown] ### Options - ○ Reject the null hypothesis; there is a significant difference. - ○ Fail to reject the null hypothesis; there is no significant difference. - ○ Reject the null hypothesis; there is no significant difference. - ○ Fail to reject the null hypothesis; there is a significant difference. --- ### Diagram Explanation #### t Distribution Chart - **Graph Description:** The graph shows a symmetric bell-shaped curve representing the t distribution. - **Degrees of Freedom Slider:** Adjust the degrees of freedom for the distribution, currently set to 21. - **Graph Highlights:** - The curve is shaded, indicating the critical regions where the null hypothesis would be rejected. This interactive chart helps determine the critical t values based on the degrees of freedom, which are essential for hypothesis testing.
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