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Elizabeth Ohene
SOCI332
APU
January 13, 2022
Assignment 3: Learning and Applying Tests of Significance T-Tests
Mock Study 1: t-Test for Independent Samples
1. Null hypothesis (H
0
): Counseling has no effect on the numbers of activities of daily living
performance.
2. Alternative hypothesis (H
1
): Counseling has effect on the numbers of activities of daily
living performance.
3. Identify your significance level (alpha)
Alpha is 0.01
4. Valid score for comparison “p.” = 0.103
5. Compare the two and apply the following rule:
0.103 > 0.01, then accept the null, i.e Counseling has no effect on the numbers of
activities of daily living performance.
Therefore, I would not recommend Counseling as a method of improving job satisfaction
as it does not help to improve job satisfaction.
Mock Study 2: t- Test for Dependent Samples
1. Null hypothesis (H
0
): Group therapy has no effect in the number of activities of daily
living performed by depressed people.
Alternative hypothesis (H
1
): Group therapy has effect in the number of activities of daily
living performed by depressed people.
2. Identify your significance level (alpha)
Alpha is 0.05
3. Valid score for comparison “p.” = 0.008
4. Compare the two and apply the following rule:
5. 0.008<0.050, then reject the null hypothesis and accept the alternative hypothesis i.e
Group therapy has effect in the number of activities of daily living performed by
depressed people because the observed difference is statistically significant at 0.05 level
of significant.
Therefore, I would not recommend Group therapy.
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Mock Study 3: One-Way ANOVA
1. Null hypothesis (H
0
): The difference in rates of TV watching does not vary by race.
Alternative hypothesis (H
1
): The difference in rates of TV watching vary by race.
2. Identify your significance level (alpha)
Alpha is 0.05
3. Valid score for comparison “p.” < .001
4. Compare the two and apply the following rule:
5. 0. 001< 0.05, then reject the null hypothesis and accept the alternative hypothesis i.e
The difference in rates of TV watching vary by race because the observed difference is
statistically significant at 0.05 level of significant.
Therefore, I would recommend the advertising firm to target each racial group
differently.
There was a statistically significant difference in rates of TV watching with respect to
race (F(2,1552) = 26.236, p < .001).
Using a t-test increases the chance of making a Type I error. So, the best way to reduce
this chance is to use an ANOVA. The ANOVA help to control Type errors such that the
Type I error is capped at 5%. However, when comparing only two means, a t-test can be
used.
Also, a T test helps in comparing of means of two groups. On the other hand, ANOVA
help in comparing of means of more than two groups.
Mock Study 4: Chi-Square Test for Independence
1. Null hypothesis (H
0
): How strong each US adults identifies with a political party does not
affect his/her level of confidence in Congress.
Alternative hypothesis (H
1
): How strong each US adults identifies with a political party
affects his/her level of confidence in Congress.
2. Identify your significance level (alpha)
Alpha is 0.05
3. Valid score for comparison “p.” = .016
4. Compare the two and apply the following rule:
5. “0. 016< 0.05, then reject the null hypothesis and accept the alternative hypothesis, i.e
How strong each US adults identifies with a political party affects his/her level of
confidence in Congress.
Therefore, observed frequency is significantly different from the expected frequency.
Political party affiliation affect one’s confidence in Congress.
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Mock Study 5: Linear Regression
1. Null hypothesis (H
0
): The mental health does not depend on age.
Alternative hypothesis (H
1
): The mental health is dependent on age.
2. Identify your significance level (alpha)
Alpha is 0.05
3. Valid score for comparison “p.” = .0005
4. Compare the two and apply the following rule:
5. “0. 0005<0.05, then accept the alternative hypothesis i.e The mental health does depend
on age. Age affects mental health.
Research shows that there is significant relationship between age and mental health.
Therefore, the researchers should continue with their study.
Part 2
Since my IV(RACE) and DV(SATFIN) are BOTH categorical variables, that is ordinal and
nominal respectively, Chi-square test shall be performed.
1. Null hypothesis H0: Race does not affect people’s perception of their financial
satisfaction.
Alternative hypothesis, H1: Race affects people’s perception of their financial
satisfaction.
2. SPSS analysis
3. Identify your significance level (alpha)
Alpha is 0.05
4. Valid score for comparison “p.” <.0001
5. Compare the two and apply the following rule:
“0. 0001< 0.05, then reject the null and accept the alternative hypothesis, i.e Race affects
people’s perception of their financial satisfaction.

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Elizabeth Ohene SOCI332 APU January 13, 2022 Assignment 3: Learning and Applying Tests of Significance T-Tests Mock Study 1: t-Test for Independent Samples 1. Null hypothesis (H0): Counseling has no effect on the numbers of activities of daily living performance. 2. Alternative hypothesis (H1): Counseling has effect on the numbers of activities of daily living performance. 3. Identify your significance level (alpha) Alpha is 0.01 4. Valid score for comparison “p.” = 0.103 5. Compare the two and apply the following rule: “0.103 > 0.01, then accept the null, i.e Counseling has no effect on the numbers of activities of daily living performance. Therefore, I would not recommend Counseling as a method of improving job satisfaction as it does not help to improve job satisfaction. Mock Study 2: t- Test for Dependent Samples 1. Null hypothesis (H0): Group therapy has no effect in the number of activities of daily living performed by depressed people. Alternative hypothesis (H1): Group therapy has effect in the number of activities of daily living performed by depressed people. 2. Identify your significance level (alpha) Alpha is 0.05 3. Valid score for comparison “p.” = 0.008 4. Compare the two and apply the following rule: 5. “0.008<0.050, then reject the null hypothesis and accept the alternative hypothesis i.e Group therapy has effect in the number of activities of daily living performed by depressed people because the observed difference is statistically significant at 0.05 level of significant. Therefore, I would not recommend Group therapy. Mock Study 3: One-Way ANOVA 1. Null hypothesis (H0): The difference in rates of TV watching does not vary by race. Alternative hypothesis (H1): The difference in rates of TV watching vary by race. 2. Identify your significance level (alpha) Alpha is 0.05 3. Valid score for comparison “p.” < .001 4. Compare the two and apply the following rule: 5. “0. 001< 0.05, then reject the null hypothesis and accept the alternative hypothesis i.e The difference in rates of TV watching vary by race because the observed difference is statistically significant at 0.05 level of significant. Therefore, I would recommend the advertising firm to target each racial group differently. There was a statistically significant difference in rates of TV watching with respect to race (F(2,1552) = 26.236, p < .001). Using a t-test increases the chance of making a Type I error. So, the best way to reduce this chance is to use an ANOVA. The ANOVA help to control Type errors such that the Type I error is capped at 5%. However, when comparing only two means, a t-test can be used. Also, a T test helps in comparing of means of two groups. On the other hand, ANOVA help in comparing of means of more than two groups. Mock Study 4: Chi-Square Test for Independence 1. Null hypothesis (H0): How strong each US adults identifies with a political party does not affect his/her level of confidence in Congress. Alternative hypothesis (H1): How strong each US adults identifies with a political party affects his/her level of confidence in Congress. 2. Identify your significance level (alpha) Alpha is 0.05 3. Valid score for comparison “p.” = .016 4. Compare the two and apply the following rule: 5. “0. 016< 0.05, then reject the null hypothesis and accept the alternative hypothesis, i.e How strong each US adults identifies with a political party affects his/her level of confidence in Congress. Therefore, observed frequency is significantly different from the expected frequency. Political party affiliation affect one’s confidence in Congress. Mock Study 5: Linear Regression 1. Null hypothesis (H0): The mental health does not depend on age. Alternative hypothesis (H1): The mental health is dependent on age. 2. Identify your significance level (alpha) Alpha is 0.05 3. Valid score for comparison “p.” = .0005 4. Compare the two and apply the following rule: 5. “0. 0005<0.05, then accept the alternative hypothesis i.e The mental health does depend on age. Age affects mental health. Research shows that there is significant relationship between age and mental health. Therefore, the researchers should continue with their study. Part 2 Since my IV(RACE) and DV(SATFIN) are BOTH categorical variables, that is ordinal and nominal respectively, Chi-square test shall be performed. 1. Null hypothesis H0: Race does not affect people’s perception of their financial satisfaction. Alternative hypothesis, H1: Race affects people’s perception of their financial satisfaction. 2. SPSS analysis 3. Identify your significance level (alpha) Alpha is 0.05 4. Valid score for comparison “p.” <.0001 5. Compare the two and apply the following rule: “0. 0001< 0.05, then reject the null and accept the alternative hypothesis, i.e Race affects people’s perception of their financial satisfaction. Name: Description: ...
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