Statistics Lab Problems 3-4: Analyzing Dependencies between Variables, Lab Reports of Statistics

Two statistics lab problems from the statistics 0200 course taught by dr. Nancy pfenning during the fall 2008 semester. The problems focus on determining dependencies between variables, specifically whether gender influences living arrangements and the relationship between height and weight. Students are asked to analyze data using minitab and interpret the results.

Typology: Lab Reports

Pre 2010

Uploaded on 09/09/2009

koofers-user-oxj
koofers-user-oxj 🇺🇸

10 documents

1 / 2

Toggle sidebar

This page cannot be seen from the preview

Don't miss anything!

bg1
Name:
Lab Problems 3-4
Statistics 0200
Fall 2008
Dr. Nancy Pfenning
3. (5 pts.) Does living on or off campus depend at all on whether a surveyed student is
male or female?
(a) What variable or variables are involved? For each variable, tell whether it is quan-
titative or categorical. Which variable (if any) should play the role of explanatory
variable?
(b) Before you even look at the data, do you expect the variables to be dependent?
If so, for which explanatory group do you expect to see a higher proportion living
on campus?
(c) Use MINITAB Basics Example U to produce a two-way table of counts and
row percents. Does one group have a considerably higher proportion on campus?
(d) Summarize your findings in one or two sentences. Be sure to express your results
specifically in terms of the variable(s) of interest, and mention to what extent the
results match your guesses in (b).
pf2

Partial preview of the text

Download Statistics Lab Problems 3-4: Analyzing Dependencies between Variables and more Lab Reports Statistics in PDF only on Docsity!

Name:

Lab Problems 3-

Statistics 0200 Fall 2008 Dr. Nancy Pfenning

  1. (5 pts.) Does living on or off campus depend at all on whether a surveyed student is male or female?

(a) What variable or variables are involved? For each variable, tell whether it is quan- titative or categorical. Which variable (if any) should play the role of explanatory

variable?

(b) Before you even look at the data, do you expect the variables to be dependent? If so, for which explanatory group do you expect to see a higher proportion living on campus?

(c) Use MINITAB Basics Example U to produce a two-way table of counts and row percents. Does one group have a considerably higher proportion on campus?

(d) Summarize your findings in one or two sentences. Be sure to express your results specifically in terms of the variable(s) of interest, and mention to what extent the results match your guesses in (b).

  1. (5 pts.) How are surveyed students’ heights and weights related?

(a) What variable or variables are involved? For each variable, tell whether it is quantitative or categorical.

Which, if any, would be the obvious choice for explanatory variable? (b) Before you even look at the data, try to make a reasonable guess for each of the following: [If you’re completely clueless, just answer with a “?”.] i. form (linear or curved): ii. direction (positive, negative, or none): iii. strength (strong, moderate, or weak): Do you expect outliers? (Explain briefly.)

(c) Use MINITAB Basics Example Q (only the relevant parts) to answer the following: Does the scatterplot show a roughly linear form? What is the regression line equation? What is the value of the correlation r? What is the typical residual size s? (d) Summarize your findings in one or two sentences. Be sure to express your results specifically in terms of the variable(s) of interest, and mention to what extent the results match your guesses in (b).