A school psychologist is interested in determining if children with attention deficit hyperactivity disorder (ADHD) learn better if English literature is read to them rather than having them read the material alone by themselves. A random sample of 10 sixth graders with ADHD is selected and divided into two groups of n=9. One of the groups has a story read to them (Listening Group) and the other reads the story alone by themselves (Reading Group). A test on the story is given after each group has finished reading or hearing the story. The following scores were obtained with 20 being a perfect score.Test the following:H0:M1=M2H1:M1 does not equal M2What do you conclude using alpha= 0.05? **Two-sample t-test, Independent Groups**This educational resource provides a detailed look at performing a two-sample t-test for independent groups. The two groups compared are the "Reading Group" and the "Listening Group" with respective scores listed below:**Reading Group:**- 10- 10- 7- 12- 8- 8- 10- 9- 11**Listening Group:**- 15- 12- 13- 11- 10- 9- 11- 10- 11### Statistical Measurement Columns:- **Count(n)**: The number of observations in each group- **Mean**: Average value of each group- **DEVSQ(SS)**: Sum of squared deviations- **STDEV.S**: Standard deviation for the sample- **df**: Degrees of freedom, total observations minus the number of groups- **S(M1-M2)**: Standard error of the mean difference between the two groups- **alpha**: Significance level for the test- **t_crit**: Critical value of t for the given degrees of freedom and significance level- **t_obs**: Observed t-value from the data- **Cohen's d**: Effect size, indicating the standardized difference between the means- **r²**: Coefficient of determination, indicating the proportion of variability explained by the group difference### Decision Columns:- The decision to either "Reject Ho" (null hypothesis) or "Fail to reject Ho" is based on the t_obs computed. Rejecting Ho indicates a statistically significant difference between the groups, while failing to reject Ho suggests no significant difference.To complete the analysis, input the relevant calculations for mean, sum of squares, standard deviation, etc., for both groups. After obtaining these values, calculate the degrees of freedom and corresponding t-values. Based on these parameter values, compare the observed t-value with the critical t-value to determine statistical significance and compute effect size metrics such as Cohen's d and r² to understand the magnitude of the difference between the two groups.

Given, The two data sets are given Reading group and listening group. n = 9 To find, test the…

Answered: A school psychologist is interested in…

Holt Mcdougal Larson Pre-algebra: Student Edition 2012

1st Edition

ISBN:9780547587776

Author:HOLT MCDOUGAL

Publisher:HOLT MCDOUGAL

Chapter11: Data Analysis And Probability

Section11.4: Collecting Data

Problem 3E

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A school psychologist is interested in determining if children with attention deficit hyperactivity disorder (ADHD) learn better if English literature is read to them rather than having them read the material alone by themselves. A random sample of 10 sixth graders with ADHD is selected and divided into two groups of n=9. One of the groups has a story read to them (Listening Group) and the other reads the story alone by themselves (Reading Group). A test on the story is given after each group has finished reading or hearing the story. The following scores were obtained with 20 being a perfect score. Test the following: H0:M1=M2 H1:M1 does not equal M2 What do you conclude using alpha= 0.05?

**Two-sample t-test, Independent Groups**

This educational resource provides a detailed look at performing a two-sample t-test for independent groups. The two groups compared are the "Reading Group" and the "Listening Group" with respective scores listed below:

**Reading Group:**
- 10
- 10
- 7
- 12
- 8
- 8
- 10
- 9
- 11

**Listening Group:**
- 15
- 12
- 13
- 11
- 10
- 9
- 11
- 10
- 11

### Statistical Measurement Columns:
- **Count(n)**: The number of observations in each group
- **Mean**: Average value of each group
- **DEVSQ(SS)**: Sum of squared deviations
- **STDEV.S**: Standard deviation for the sample
- **df**: Degrees of freedom, total observations minus the number of groups
- **S(M1-M2)**: Standard error of the mean difference between the two groups
- **alpha**: Significance level for the test
- **t_crit**: Critical value of t for the given degrees of freedom and significance level
- **t_obs**: Observed t-value from the data
- **Cohen's d**: Effect size, indicating the standardized difference between the means
- **r²**: Coefficient of determination, indicating the proportion of variability explained by the group difference

### Decision Columns:
- The decision to either "Reject Ho" (null hypothesis) or "Fail to reject Ho" is based on the t_obs computed. Rejecting Ho indicates a statistically significant difference between the groups, while failing to reject Ho suggests no significant difference.

To complete the analysis, input the relevant calculations for mean, sum of squares, standard deviation, etc., for both groups. After obtaining these values, calculate the degrees of freedom and corresponding t-values. Based on these parameter values, compare the observed t-value with the critical t-value to determine statistical significance and compute effect size metrics such as Cohen's d and r² to understand the magnitude of the difference between the two groups.

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