Instructions, Part 2
Using the Unit 1_Case.xlsx, conduct analysis of
relationships between variables. Be sure to use the correct methods for
categorical or quantitative variables. For categorical variables, use the
crosstabulation analysis. For quantitative variables, use the correlation and
regression. Indicate what the correlations are and state and interpret the
estimated linear regression equations. Include r-squared as a measure of
explained variability in Amount $. Interpret your results based on the
following case problem:
You are a marketing representative for a major credit card
company. You have successfully examined the distributions of each variable in
your sample data to get a better idea of the population distributions. Now, you
speculate that there are possibly relationships between variables.
Specifically, you consider the relationship between income and amount charged,
age and amount charged, and household size and amount charged. You are trying
to determine if these quantitative variables are good predictors of amount
charged. Simple linear regression is the analysis you use to do this. Next, you
consider the relationships between gender and amount charged and then education
level and amount charged. When using the categorical variables gender and
education, you consider whether those variables are predictors of amount
charged. Use the variable CodedAmt as the dependent variable (D.V.). The
independent variables (I.V.) would be gender and EdLevel.
In 2-3 well-written paragraphs, you then need to summarize
your findings. Prior to your summary, as in Case 1, all of your output will be
reported and key insights noted. Be sure to include these insights below each
section of your statistical output.
Report Format
The following format is common to all of the cases this
term. First, include an introduction. Briefly discuss what is included in the
report. Also, list all variables used, what type of variable each is
(quantitative or categorical), and whether it is an I.V. or D.V. Also, include
a brief description of statistical methods you will use. Here, for example, you
are using histograms and descriptive statistics to examine the distributions of
quantitative variables. You are using frequency tables and bar graphs/pie
charts to examine the distributions of categorical variables. Further, you are
using regression analysis to examine the relationship of quantitative I.V.s and
the quantitative D.V., Amount $. You are using cross tab analysis to examine
the relationship between categorical I.V.s and the categorically coded D.V.,
CodedAmt.
The next section is called analysis. In this section include
all of your output. Label all figures and tables. After each analysis include a
brief statement of what the analysis shows in terms of your research questions.
Finally, include a results section. At the end of your
report, the results section summarizes the important results of your analysis.
Example of Analysis
Figure 1. Histogram of Age of Cardholders
M = 35.54 SD =
9.7 N = 50
The distribution of ages appears to be approximately normal.
There are no outliers present. Over half of the cardholders in this sample
(52%) are between the ages of 26 and 42.
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