16.2 31.1 25.3 24.8 23.8 8.0 27.2 24.0 38.8 51.5 28.0 26.5 8.3 43.1 29.7 39.3 18.7 28.2 17.9 33.1 25.6 5.4 39.4 29.2 41.1 15.8 24.3 32.0 25.8 52.4 17.1 33.0 30.1 23.2 19.1 24.3 4.8 36.7 11.1 40.9 28.8 27.9 46.8 36.7 11.5 32.4 38.0 26.1 25.3 39.2 23.8 23.4 27.9 44.6 27.5 35.3 34.5 11.9 25.6 27.3 28.0 24.8 16.5 13.6 34.2 34.8 21.2 31.0 24.9 31.3 35.0 27.5 42.2 37.8 49.5 31.2 29.0 26.1 26.5 25.6 17.5 29.7 23.9 18.5 37.3 7.4 30.8 14.0 25.7 37.8 32.0 20.4 6.9 19.8 45.7 29.3 18.4 56.3 35.4 0.9 22.9 BMI data Obesity is a risk factor for many health problems s uch as type 2 diabetes, high blood pressure, joint problems, and gallstones. Using data collected in 2 018 through the National Health and Nutrition Examination Survey, the National Institute of Diabe tes and Digestive and Kidney Diseases estimates tha t 37.7% of all adults in the United States have a bod y mass index (BMI) in excess of 30 and so are categorized as obese. The data in the file Obesity (from the textbook but also posted) is consistent with these findings. a. Use the Obesity data set to develop a point estimate for the BMI f or adults in the United States. Are adults in the United States obese on average? b. What is the sample standard deviation? c. Develop a 95% confidence interval for the BMI of adults in the United States.
Inverse Normal Distribution
The method used for finding the corresponding z-critical value in a normal distribution using the known probability is said to be an inverse normal distribution. The inverse normal distribution is a continuous probability distribution with a family of two parameters.
Mean, Median, Mode
It is a descriptive summary of a data set. It can be defined by using some of the measures. The central tendencies do not provide information regarding individual data from the dataset. However, they give a summary of the data set. The central tendency or measure of central tendency is a central or typical value for a probability distribution.
Z-Scores
A z-score is a unit of measurement used in statistics to describe the position of a raw score in terms of its distance from the mean, measured with reference to standard deviation from the mean. Z-scores are useful in statistics because they allow comparison between two scores that belong to different normal distributions.
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