# Critical thinking

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 age of the women in the Gestation Demographics SEU dataset.

We will be testing the hypothesis that the mean age (? = ?0) for women is 37 years in the Gestation Demographics SEU dataset. The topic of hypothesis testing was introduced in HCM505. If you need a review see Chapter 7 of our text.

1. 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)

## Expert Solution Preview

Introduction: In this assignment, we will be exploring the Gestation Demographics SEU dataset and performing some statistical analysis using R Studio or Excel. Specifically, we will be creating a histogram to visualize the age distribution of women after giving birth to their first child, calculating the mean age of the women in the dataset, and testing a hypothesis regarding the mean age of women giving birth.

1. To create a histogram of the age distribution of women after giving birth to their first child, we first need to extract the relevant data from the dataset. In R Studio, we can do this using the following code:

“`{r}
gestation_data

#Critical #thinking

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