Two way ANOVA and Assessment statistics homework help


For this Assignment, you use two-way ANOVA with interaction. Be sure to complete all of the parts of the assignment listed below. As this is an ANOVA, you also use multiple comparisons to determine for which factors the differences are significant. Also, to avoid additional type 1 errors, you must use Tukey, one of a number of possible methods to adjust for your multiple comparisons.

The Assignment
  1. Provide numeric descriptive statistics (include skewness and kurtosis if appropriate) and graphic descriptions for Sex, Educ, and Exercise.
  2. Create histograms of the number of steps (Exercise) (dependent variable) for each combination of levels for the two independent variables. Describe the data and shape of the distributions.
  3. Discuss whether the assumptions of homogeneity of variance of the groups and normality of the data on Exercise are met. Be sure to include output to support your decision on whether the assumptions have been met. (Continue with the analyses even if assumptions are not met)
  4. Conduct two-way ANOVA with interaction and post hoc analysis (as appropriate) using Tukey to correct for multiple comparisons. Provide relevant SPSS output.
  5. Interpret the analysis results in the context of the research question: Is there a difference in the level of exercise based on a person’s sex and level of education? Include important statistics from your analysis results to support your conclusion and generalize your results, if appropriate, to the relevant population(s).


For this Assignment, you test that assumptions for multiple linear regression have been met, use SPSS to create a multiple linear regression, evaluate results to determine whether the model is appropriate, and finally interpret the relationships uncovered through this statistical test between the independent and dependent variables. Use the Week 4 Dataset (SPSS document) from the Learning Resources area to complete this assignment.

The Assignment
  1. Explain the assumptions of Linearity, Sampling independence, Normality, and Homoscedasticity (or equal variance).
    1. How would you test whether these have been met?
    2. Using SPSS, test the assumption of Linearity between the independent and dependent variables.
    3. Using SPSS, test the assumption of Normality for the dependent variable.
  2. Conduct a multiple linear regression using SPSS. Provide relevant SPSS output and assess the statistical significance of the effects of mother’s Age, BMI, and Coffee (Cups per Day) on Birth weight.
  3. Explain the practical implications of your finding. Include a reference to the R square of the model in your discussion.
  4. Discuss whether or not there is interaction (effect modification) first between Age and BMI and second between BMI and Coffee.


Daniel, WW & Cross, CL. (2013). Biostatistics: A Foundation for Analysis in the Health Sciences. Hoboken, NJ: Wiley.

  • Chapter 8, “ Analysis of Variance” ( pp. 304 –412)

Daniel, WW & Cross, CL. (2013). Biostatistics: A Foundation for Analysis in the Health Sciences. Hoboken, NJ: Wiley.

  • Chapter 9 ,“Simple Linear Regression” ( pp. 413 –488)
  • Chapter 10, “Multiple Regression and Correlation” ( pp. 489 –538

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