10.1.2: Quantitative Variable Analysis

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Semester Project – Assignment 2 Analyzing a Quantitative Variable (Rental Prices)

In this project assignment, you will perform a thorough analysis the quantitative variables you collected in your Sampling and Data Project: the rental prices for 1-bedroom apartments and their square footage.

Using Excel or another tool, you’ll create frequency tables, visual summaries (histogram and boxplot), and calculate relevant descriptive statistics including mean, median, standard deviation, and five number summary. You’ll use these tools to describe the shape, center, and spread of your data, and interpret your findings in plain language.

Objectives

Construct a frequency table and histogram
Construct a boxplot and identify potential outliers
Describe distribution shape (modality, skew), center, and spread
Calculate and interpret key statistics: mean, median, range, standard deviation, and five number summary
Use technology to support analysis

Assignment Steps

Locate your files from part 1 and save copies using the names shown at the bottom of these directions.
Correct any issues that caused you to lose points in part 1.
All calculations will go in your Excel file and all written responses will be included in your Word document.
Create a single frequency table for rental prices using 5 to 10 evenly spaced class intervals.
1. This should include all 80 values from the sample data.
2. The class width should be a nice number
3. The first class should start at a multiple of the class width
4. Formulas should be used to calculate the frequencies
Create a histogram from the frequency table in Excel. Your histogram should include:
- A meaningful chart title
- Clearly labeled axes
- Equal-width bins/classes
Create a boxplot for rental price data to visually assess spread and potential outliers.
Calculate the following descriptive statistics:
- Mean
- Median
- Standard Deviation
- Range
- Five number summary
- IQR
- Fences for identifying outliers
Repeat #4-7 for the square footage variable
Summarize the distribution of each variable. This should be a paragraph or two for each added to your Word document. Include:
- Shape of the distribution (modal shape, skewness)
- List outliers, explain what they might represent, decide if you want to remove them and why.
- Comparison of mean and median
- What the spread tells you about market variability
Real-World Interpretation: What does this data tell us about 1-bedroom rental prices in Lakewood and the other city you chose? Who might use this information and why? Are any listings significantly higher or lower than average, and what might that mean?
Circle back to the question you wrote in the data collection part of the project: Answer any of the questions you posed in part 1 and acknowledge if you cannot answer them.

Helpful Tips

Class intervals in your histogram should be equal-width, non-overlapping, and intuitive (e.g., $100 increments)
Use labels: Axis titles and legend titles should match your variable name exactly
The boxplot is great for visualizing skewness and identifying any extreme outliers
If your mean is much higher than your median, that might signal right skew (a few expensive listings pulling up the average)

Submission Instructions

Submit your Excel file with the sample data and all calculations, tables, and graphs
File name format (Excel): LastName_Part2.xlsx
Submit your Word document with the written responses from parts 1 and 2
File name format (Word): LastName_Part2.docx
Upload to the Project Assignment in our LMS

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