Observational studies have suggested that low dietary intake or low plasma concentrations of retinol, beta-carotene, or other carotenoids might be

 Observational studies have suggested that low dietary intake or low plasma concentrations of retinol, beta-carotene, or other carotenoids might be associated with increased risk of developing certain types of cancer. However, relatively few studies have investigated the determinants of plasma concentrations of these micronutrients. A cross-sectional study was conducted to investigate the relationship between personal characteristics and dietary factors, and plasma concentrations of retinol, beta-carotene and other carotenoids. Study subjects (N = 315) were patients who had an elective surgical procedure during a three-year period to biopsy or remove a lesion of the lung, colon, breast, skin, ovary or uterus that was found to be non-cancerous.

The data from this experiment are in a xlsx file that is part of the In-Class Assignment. Once you have downloaded this file, you can open it using Excel.

The following variables are included in the file: AGE (years); SEX (1=Male, 2=Female); SMOKSTAT (1=Never, 2=Former, 3=Current Smoker); QUETELET (BMI, weight/height2); VITUSE (vitamin use; 1="Yes, fairly often", 2="Yes, not often", 3="No"); CALORIES (Number of calories consumed per day); FAT (Grams of fat consumed per day); FIBER (Grams of fiber consumed per day); ALCOHOL (Number of alcoholic drinks consumed per week); CHOLESTEROL [Cholesterol consumed (mg per day]; BETADIET [Dietary beta-carotene consumed (mcg per day)]; RETDIET [Dietary retinol consumed (mcg per day)]; BETAPLASMA [Plasma beta-carotene (ng/ml)]; and RETPLASMA [Plasma Retinol (ng/ml)].

Analyze the RETPLASMA variable. Use the "Explore Quantitative Data" app to describe the data for each gender.

(Attach graphs and descriptive statistics here)

Using the mean, standard deviation and sample size, calculate a 95% confidence interval for the mean for males and females. Verify that the 95% confidence interval for the mean for both males and females is correct using the "Inference for a Mean" app. Interpret both confidence intervals. 

Are these confidence intervals consistent with the graphs that you produced? 

Do you have any concerns about the confidence intervals that you generated? Explain.

Conduct a test for each sex to determine if the variable you chose differs from normal values. Normal values for retinol are 800 ng/ml. Use the same "Inference for a Mean" app.

Discuss any concerns you might have with the results of your hypothesis tests.