Part
1: Primary Data Analysis
1.What
statistics will explain your situation? What graphs, charts, or tables will
help readers understand your points? A minimum of two references to outside
sources such as data from a newspaper/journal article, research study,
university/corporate report, or national data set.
a) A
description of the historical and practical context, variables, units,
terminology, and example/application to the real world.
b) Clearly
defined dependent and independent variables
c) Levels
of measurement of the variables (nominal, ordinal, interval, ratio)
d)Sampling
methodology
e) A
minimum of one of each, preferably more: confounding, lurking, and missing variables.
State the problems you might encounter with missing variables or information.
f) Experimental
or observational study; qualitative or quantitative research
g) One
or more graphs, charts, images to give the reader a visual understanding of the
background of the topic.
h) A
description of the information you collect and how it relates to the big
picture of social and economic trends.
Part
2: Examination of Descriptive Statistics
2.
Your next step is to collect organize, and
examine
the data. This section is designed to present the
calculations,
graphs, and explanation of what you have found.
Since
all inferential tests are based on several assumptions, before you
conduct
the inferential statistics, you want to make sure that you are not violating
any assumptions. In Part 2, you need to answer the following questions:
A) Are the scores normally distributed? Construct a histogram, scatterplot,
frequency polygon, or other graph to show the nature,
shape, or distribution of the data to include in your paper.
This graph will appear in the body of the paper.
After your inspection, you must perform calculations or use
statistics to confirm normality, outliers, and information about the distribution.
B) Find the mean, median, and mode. These
Measures
of Central Tendency can help you better understand and
describe
your data.
C) Variation: Find the range, variance, and standard deviation.
These
Measures
of the Variation show the spread of the data. Describe the dispersion or the
amount that the sample values vary among themselves.
You
might also want to use the five number summary and provide a boxplot to
consider your data or use
percentiles
and other measures of spread.
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