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Construct a research question using the General Social Survey dataset, which can

ID: 2931515 • Letter: C

Question

Construct a research question using the General Social Survey dataset, which can be answered by a Pearson correlation and bivariate regression.

Use SPSS to answer the research question. Post your response to the following:

What is your research question?

What is the null hypothesis for your question?

What research design would align with this question?

If you found significance, what is the strength of the effect?

I used data from the High School Longitudinal Survey to conduct the tests, whose results are below.

Table 8.0

Correlations

Years math teacher has taught high school math

T2 Scale of student's mathematics self-efficacy

Years math teacher has taught high school math

Pearson Correlation

1

.028**

Sig. (2-tailed)

.001

N

17020

14482

T2 Scale of student's mathematics self-efficacy

Pearson Correlation

.028**

1

Sig. (2-tailed)

.001

N

14482

19771

**. Correlation is significant at the 0.01 level (2-tailed).

Table 8.1

Variables Entered/Removeda

Model

Variables Entered

Variables Removed

Method

1

T2 Scale of student's mathematics self-efficacyb

.

Enter

a. Dependent Variable: Years math teacher has taught high school math

b. All requested variables entered.

Table 8.2

Model Summary

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

1

.028a

.001

.001

8.519

a. Predictors: (Constant), T2 Scale of student's mathematics self-efficacy

Table 8.3

ANOVAa

Model

Sum of Squares

df

Mean Square

F

Sig.

1

Regression

806.152

1

806.152

11.107

.001b

Residual

1050975.028

14480

72.581

Total

1051781.180

14481

a. Dependent Variable: Years math teacher has taught high school math

b. Predictors: (Constant), T2 Scale of student's mathematics self-efficacy

Table 8.4

Coefficientsa

Model

Unstandardized Coefficients

Standardized Coefficients

t

Sig.

B

Std. Error

Beta

1

(Constant)

10.266

.071

144.872

.000

T2 Scale of student's mathematics self-efficacy

.234

.070

.028

3.333

.001

a. Dependent Variable: Years math teacher has taught high school math

Correlations

Years math teacher has taught high school math

T2 Scale of student's mathematics self-efficacy

Years math teacher has taught high school math

Pearson Correlation

1

.028**

Sig. (2-tailed)

.001

N

17020

14482

T2 Scale of student's mathematics self-efficacy

Pearson Correlation

.028**

1

Sig. (2-tailed)

.001

N

14482

19771

**. Correlation is significant at the 0.01 level (2-tailed).

Explanation / Answer

What is your research question?

The research question is given as below:

Is there any statistically significant linear relationship exists between the dependent variable or response variable years math teacher has taught high school math and independent variable or explanatory variable T2 scale of student’s mathematics self-efficacy?

What is the null hypothesis for your question?

The null hypothesis for the test is given as below:

Null hypothesis: H0: There is no any statistically significant linear relationship exists between the dependent variable or response variable years math teacher has taught high school math and independent variable or explanatory variable T2 scale of student’s mathematics self-efficacy.

Alternative hypothesis: Ha: There is a statistically significant linear relationship exists between the dependent variable or response variable years math teacher has taught high school math and independent variable or explanatory variable T2 scale of student’s mathematics self-efficacy.

H0: = 0 Vs Ha: 0

What research design would align with this question?

We would align the correlational and regression analysis for the given scenario.

If you found significance, what is the strength of the effect

For the given scenario, the correlation coefficient found to be statistically significant at the 1% level of significance. There would be high strength of the effect or response variable.