MATH1324 Assignment 1

Modeling Body Measurements

Student Details

Student Name: Hari Krishnan (s3797479)

Problem Statement

I have chosen the variable biacromial diameter (cms) as the body measurement to check whether it fits normal distribution.I have checked this separately for men and women.

The steps taken for normal distribution fitting are 1) Check Mean = Meadin then it is symmetric and bell shaped. SD is small then the curve is tall 2) Skewness =0 and kurtosis =3 then it is double confirmed that the distribution is normal 3) Histogram bell shaped 4) Box Plot mean and median in the middle of the box (Symetric) 5) Central limit theorem states If the underlying population distribution of a variable is normally distributed, the resulting sampling distribution of the mean will be normally distributed.When the sample size is large, typically defined as n>30, then sampling distribution of the mean is approximately normal, regardless of the variable’s underlying population distribution Finally if the variable is nortmally distributed then the insight is ## we will take a large sample of n >30

Load Packages

# This is a chunk where you can load the necessary packages required to reproduce the report

Data

Import the body measurements data and prepare it for analysis. Show your code.

# This is a chunk for your Data section. 

Summary Statistics

Calculate descriptive statistics (i.e., mean, median, standard deviation, first and third quartile, interquartile range, minimum and maximum values) of the selected measurement grouped by sex.

# This is a chunk for your Summary Statistics section. 

Distribution Fitting

Compare the empirical distribution of selected body measurement to a normal distribution separately in men and in women. You need to do this visually by plotting the histogram with normal distribution overlay. Show your code.

# This is a chunk for your Distribution Fitting section. 

Interpretation

Going back to your problem statement, what insight has been gained from the investigation? Discuss the extent to how your theoretical normal distribution fits the empirical data.