ordinal/categorical, continuous, and dichotomous variables. Using the Gestation Demographics SEU dataset

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)Ensure to submit the following requirements for the assignment:

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.

  1. Always use a title page, an introduction, a discussion where you interpret the meaning of the histogram, and a conclusion should be included.

Expert Solution Preview

Introduction:

In this assignment, we will analyze the Gestation Demographics SEU dataset using R Studio or Excel. We will perform a simple distribution graph to explore the age of women after giving birth to their first child. We will also determine the mean age of the women in the dataset and test the hypothesis that the mean age for women is 37 years.

1. How do we create a simple distribution graph (histogram) for the age of women after giving birth to their first child?

To create a simple distribution graph for the age of women after giving birth to their first child, we can use R Studio or Excel. We will first select the age variable from the Gestation Demographics SEU dataset and create a frequency table. We will then use this frequency table to create a histogram, which consists of parallel vertical bars that show the frequency distribution of the quantitative variable in the graph. The area of each bar is equal to the frequency of items found in each class. The resulting histogram will show the distribution of ages for women after giving birth to their first child.

2. What is the mean age of the women in the Gestation Demographics SEU dataset?

To determine the mean age of the women in the Gestation Demographics SEU dataset, we can use R Studio or Excel. We will select the age variable from the dataset and calculate the mean using the appropriate formula. The resulting value will be the mean age of the women in the dataset.

3. What is the hypothesis being tested in this assignment and how do we determine whether to accept or reject it?

The hypothesis being tested in this assignment is that the mean age for women is 37 years in the Gestation Demographics SEU dataset. The null hypothesis is that the mean age of women giving birth is 37 years old, and the alternative hypothesis is that the mean age of women giving birth is not 37 years old. To determine whether to accept or reject this hypothesis, we will perform a hypothesis test using a significance level of 0.05. If the p-value is less than or equal to 0.05, we will reject the null hypothesis and conclude that the mean age for women is not 37 years in the dataset. If the p-value is greater than 0.05, we will accept the null hypothesis and conclude that the mean age for women is 37 years in the dataset.

#ordinalcategorical #continuous #dichotomous #variables #Gestation #Demographics #SEU #dataset

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