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Deep Understanding in Descriptive Statistics

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Problem 2.28 is what needs solved. 2.27 is provided for reference because the problem refers to it.

Nutrition

The food-frequency questionnaire (FFQ) is an instrument often used in dietary epidemiology to assess consumption of specific foods. A person is asked to write down the number of servings per day typically eaten in the past year of over 100 individual food items. A food- composition table is then used to compute nutrient intakes (protein, fat, etc.) based on aggregating responses for individual foods. The FFQ is inexpensive to administer but is considered less accurate than the diet record (DR) (the gold standard of dietary epidemiology). For the DR, a participant writes down the amount of each specific food eaten over the past week in a food diary and a nutritionist using a special computer program computes nutrient intakes from the food diaries. This is a much more expensive method of dietary recording. To validate the FFQ, 173 nurses participating in the Nurses' Health Study completed 4 weeks of diet recording about equally spaced over a 12- month period and an FFQ at the end of diet recording [11]. Data are presented for saturated fat, total fat, total alcohol consumption, and total caloric intake for both the DR and FFQ. For the DR, average nutrient intakes were computed over the 4 weeks of diet recording. Table 2.16 shows the format of this file.

2.27) Use descriptive statistics to relate nutrient intake for the DR and FFQ. Do you think the FFQ is a reasonably ac-curate approximation to the DR? Why or why not?
2.28) A frequently used method for quantifying dietary intake is in the form of quintiles. Compute quintiles for each nutrient and each method of recording, and relate the nutrient composition for DR and FFQ using the quintile scale. (That is, how does the quintile category based on DR relate to the quintile category based on FFQ for the same individual?) Do you get the same impression about the concordance between DR and FFQ using quintiles as in Problem 2.27, in which raw (ungrouped) nutrient intake is considered? In nutritional epidemiology, it is customary to assess nutrient intake in relation to total caloric intake. One measure used to accomplish this is nutrient density, which is defined as 100% × (caloric intake of a nutrient/ total caloric intake). For fat consumption, 1 g of fat is equivalent to 9 calories.

These are 5x5 tables that you create to show the number of people classified into a particular combination of quintile categories. For each table the rows represent the quintiles of the DR and the columns represent quintiles of the FFQ. Look to see whether there is a weak or strong concordance between the measures and whether there is agreement for the measures.

Table 2.16 attached
Data set attached

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Solution Summary

The solutions gives detailed discussion on some measurements of descriptive statistics. The topic includes DR, FFQ, quantiles and concordance. The conecpts, graphs and tables are put together for better understanding.

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The sales manager of your company wishes to evaluate the performance of the company's sales representatives.

See attached files for full problem description.

The sales manager of your company wishes to evaluate the performance of the company's sales representatives. Each sales representative is solely responsible for one sales territory. You and the manager believe that sales performance substantially depends on the above collected data. The manager has asked you to analyze this data to identify "good" and "bad" sales representatives. Questionable representatives whose performance is substantially lower will get special training aimed at improving their sales techniques.

Analyze this data, i.e., calculate descriptive statistics--mean, standard deviation, and so on, and create tables and graphs. WARNING: Before starting, develop a "game plan" to analysis the data, i.e., ask yourself what is the goal of your analysis. The managerial report should summarizing the results of your analysis. The report should only contain the key statistical information, in non-technical terms. Try to include tables, figures, graphs as part of the report. AND talk to the graphs/figures/tables-i.e., what is in them that's so important?? Use bullets!! Include the other frequency distributions, descriptive statistics not in the report in an appendix. Further guidelines to writing the report are on the last page.

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