NURS 8200 Assignment 5 Linear Regression

NURS 8200 Assignment 5 Linear Regression

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 NURS 8200 Assignment 5 Linear Regression

 

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NURS 8200 Assignment 5 Linear Regression Answers 

Simple Linear Regression

  1. What is the total sample size?

The sample size is 378

  1. What is the mean income and mean number of hours worked?

The mean for income and the number of hours worked are $1,485.49 and 33.52 respectively.

  1. What is the correlation coefficient between the outcome and predictor variables? Is it significant? How would you describe the strength and direction of the relationship?

The correlation coefficient between the outcome and predictor variable is 0.3; this indicates a weak positive correlation.

  1. What it the value of R squared (coefficient of determination)? Interpret the value.

The value of R squared is 0.088. This means that there is a weak effect size with only 8.8% of the data fitting in the model.

  1. Interpret the standard error of the estimate? What information does this value provide to the researcher?

The standard error of the estimate is $907.877; this indicates a high level of variation in the regression model.

  1. The model fit is determined by the ANOVA table results (F statistic = 37.226, 1,376 degrees of freedom, and the p value is .001). Based on these results, does the model fit the data? Briefly explain. (Hint: A significant finding indicates good model fit.)

The model fit because the p-value is smaller than the critical alpha, p=0.05.

  1. Based on the coefficients, what is the value of the y-intercept (point at which the line of best fit crosses the y-axis)?

The value of y-intercept is 711.651.

  1. Based on the output, write out the regression equation for predicting family income.

The regression equation =Family income = 711.651 + 23.083 hours worked per week.

  1. Using the regression equation, what is the predicted monthly family income for women working 35 hours per week?

The predicted monthly family income=711.651 + 23.083*35 = 1519.556

  1. Using the regression equation, what is the predicted monthly family income for women working 20 hours per week?

The predicted monthly income for a working for 20 hours per week = 711.651+ 23.083* 20 =1,173.311.

 

Part 2

  1. Analyze the data from the SPSS output and write a paragraph summarizing the findings. (Use the example in the SPSS output file as a guide for your write-up.)

The findings indicates that age, education attainment, currently employed and the number and types of abuse predict the CES-D scores. The correlation coefficient value was r=0.412. The model fits the relationship between the predictor and outcoem variables, F=31.506, sig.000.

  1. Which of the predictors were significant predictors in the model?

The CES-D score was significantly correlated to the number and types of abuses (0.37).

  1. Which of the predictors was the most relevant predictor in the model?

The number and types of abyuse was the more relevant predictor.

  1. Interpret the unstandardized coefficents for educational attainment and poor health.

The unstandardized coefficient values indicate a strong correlation between the poor health self rating and the CES-D scores. The Beta value was 10.928.

  1. If you wanted to predict a woman’s current CES-D score based on the analysis, what would the unstandardized regression equation be? Include unstandardized coefficients in the equation.

The unstandarized regression equation will be:

CES-D score = 18.165 + 0.068 respondents age at the time of interview – 2.518 educational attainment – 3.605 currently employed +9.496 poor health rating + 3.432 number and types pfabuses.

 

 

 

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