**Critical Thinking Assignment (105 points)**

This week we are learning about ordinal/categorical, continuous, and dichotomous variables. Using the Gestation Demographics SEU dataset that is located in the tabs at the bottom of the __Framingham dataset__ provided, perform the following problems using R Studio or Excel.

- Create a simple distribution graph (histogram) where we will explore the age of women after giving birth to their first child. Remember that a histogram consists of parallel vertical bars that show the frequency distribution of a quantitative variable in the graph. See the example in
*Introductory Statistics with R* on pages 71-7 or pages 123-124 in *EXCEL statistics A quick guide.* The area of each bar is equal to the frequency of items found in each class.
- Determine the mean of the age of the women in the Gestation Demographics SEU dataset.
- We will be testing the hypothesis that assumes the mean age (μ = μ0) for women is 37 years in the Gestation Demographics SEU dataset.

H0 The mean age of women giving birth is 37 years old. (Null Hypothesis)

H1 The mean age of women giving birth is not 37 years old. (Alternative Hypothesis)

Present your findings in a Word document, by copying and pasting the histogram into the document. After your analysis state whether you accept or reject the null hypothesis and your reasoning why. Always use a title page, an introduction, a discussion where you interpret the meaning of the histogram, and a conclusion should be included. Your submission should be 2-3 pages to discuss and display your findings.

Provide support for your statements with in-text citations from a minimum of two scholarly, peer-reviewed articles. One of these sources may be from the class readings, textbook, or lectures, but the others must be external. The Saudi Digital Library is a good place to find these sources and should be your primary resource for conducting research.

Follow APA and Saudi Electronic University writing standards.

Review the grading rubric to see how you will be graded for this assignment.

You are strongly encouraged to submit all assignments to the TurnItIn Originality Check prior to submitting them to your instructor for grading.

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