Statistics
Outline of Material to Present

Part 1: Collection of Data – Introduction and Primary Data Analysis (3 – 5 paragraphs):
1. Describe the objective: Before you can examine the data, you must understand the problem.
a. Discuss the importance of this issue or situation.
b. Introduce the company or organization you are preparing this report for, and explain
why it is important to them.
c. What is the research question? In other words, what is the basic question you, as the
researcher, want to address? Why should we care about it?
d. Was this an experimental or observational study? Explain.
2. Clearly and with sufficient detail, describe the population, sample, and collection methods in
this study.
a. What is the population you are interested in?
b. What is the sample, specifically?
c. What is a plausible way the sample was chosen and why?
d. What problems or biases might have occurred from choosing that type of sampling
method?
3. Discuss the type of data.
a. Was the data quantitative or qualitative? Explain.
b. What is the level of measurement (nominal, ordinal, interval and ratio)? Explain.
4. Describe the variables
a. What are the independent and dependent variables? Give the type, units, and more
specific information.
b. Give examples of any confounding variables, lurking variables, and/or missing variables
and explain how they may be affecting your study.
Part 2: Organization of Data – Examination of Descriptive Statistics (graphs and tables, and
approximately 4 paragraphs)
Now that your data is collected, you need to organize it to identify characteristics and patterns.
1. Graph your data appropriately. Construct a scatterplot, bar graph, or other graph to show
the nature of the data. For each graph, be sure you label the graph completely – that means
give it a title, label the axes, and explain what that graph means in the context of this
narrative.
2. Discuss whether the data is normally distributed. For this, use a visual inspection of a

Histogram and Normal Quantile Plot, as well as what you see in the data itself and what that
means about the high and low ends of the data.
3. Calculate and present the three Measures of Central Tendency: mean, median, and mode.
Provide both the value of the statistics as well as an analysis of what they mean in terms of
understanding the sample.
4. Calculate and present the Measures of Variation: range and standard deviation. Provide both
the value of the statistics as well as an analysis of what they mean in terms of understanding
the sample.
5. Calculate and present the 5-Number Summary: minimum, Q1, median, Q3, maximum.
Provide both the value of the statistics as well as an analysis of what they mean in terms of
understanding the sample.
6. Identify any Outliers. You can do this using a visual inspection of the graph as well as the
formulas from the textbook (HINT: Q1 – 1.5*IQR, and Q3 + 1.5*IQR).
7. Discuss any corrections: Based on your inspection of the outliers are there any errors that
should be corrected? How would you correct them? Discuss the implications of this result.
Part 3: Analysis of Data – Examination of Inferential Statistics (tables of results, and appropriate
hypothesis test steps)
Assuming that all assumptions have been met, it is now time to analyze the data. Present a complete
hypothesis test.
1. Identify the claim.
2. State the null and alternative hypotheses, in words and in symbolic form.
3. Explain what type of test you will be performing (i.e. a test of two dependent means, a test for
correlation, etc.) and why that test is appropriate to address the main question you are trying to
answer.
4. Select the significance level and determine if it is a one or two-tailed test.
5. Identify the test statistic and compute the value of the test statistic and the p-value.
6. Make a decision of whether to Reject or Fail to Reject the null hypothesis.
7. Restate your decision in nontechnical terms. That means, state your conclusion in a way that
anyone can understand; a final conclusion that just says “reject the null hypothesis” by itself
without explanation is not helpful to those who hired you. Explain in ordinary terms what it
means.
Part 4: Conclusion and Recommendations (approximately 3 paragraphs)
Summarize and explain your results. Provide recommendations.
1. What can you infer from the statistics?
2. What information might lead you to a different conclusion?
3. What variables are missing?
4. What additional information would be valuable to help draw a more certain conclusion?
5. What qualitative or quantitative data would you want to collect if you were hired to do a follow
up study