Distribution Graph (Histogram)

After 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.

  1. 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.
  2. Determine the mean of the age of the women in the Gestation Demographics SEU dataset.
  3. We will be testing the hypothesis that assumes the mean age (μ = μ0) for women is 32 years in the Gestation Demographics SEU dataset.

H0 The mean age of women giving birth is 32 years old. (Null Hypothesis)

Don't use plagiarized sources. Get Your Custom Essay on
Distribution Graph (Histogram)
Just from $13/Page
Order Essay

H1 The mean age of women giving birth is not 32 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.
  • 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. not including title page and reference page
  • Provide support for your statements with in-text citations from a minimum of two scholarly, peer-reviewed articles.
  • Follow APA 7th edition .
  • should be following in text citation and referencing reules

ORDER NOW »»

and taste our undisputed quality.