Take a sample of 100 homes for sale in your home town. (please use zip cose 18964 for this portion ) Information about homes can be found on websites such as Realtor, Zillow, and Trulia. For each home, record the address, zip code, current price, number of bedrooms, number of bathrooms, square footage, and the company of the listing agent. The use of EXCEL or other data software may be beneficial. You will be creating a 2-3 page report describing the housing market in your home town.
Write an introduction that includes the context of the data that has been collected. The introduction should include an identification of who, what, where, how, and why.
Create frequency tables to organize the responses of EACH variable. For quantitative variables, it may be appropriate to bin data into groups; for example, you may wish to group home prices into bins of width 25k or 50k. The variables are highlighted in green above.
Accompany each frequency table with an appropriate display/chart. Write a sentence that describes the distribution represented in each display. The description should include the context of the report.
Create a contingency table that compares the variables “zip code” and “company”. Accompany your contingency table with an appropriate display. Describe the marginal distribution of “zip code”.
Group your data by zip code and create a boxplot and 5-number summary describing the current home prices in each area. Note any outliers that may be present using the “fence” method.
Write a sentence describing the distribution of home prices using the 68%-95%-99.7% rule. Then comment on whether or not this rule is appropriate in estimating the distribution of home prices.
Write a conclusion summarizing the report.
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INTRODUCTION:
The data collected for this report is based on a sample of 100 homes for sale in the home town with a zip code of 18964. The information about these homes was gathered from websites such as Realtor, Zillow, and Trulia. The variables recorded for each home include the address, zip code, current price, number of bedrooms, number of bathrooms, square footage, and the company of the listing agent. This report aims to provide an overview and analysis of the housing market in the home town using the collected data.
FREQUENCY TABLES AND CHARTS:
1. Home Prices:
- Frequency Table:
Price Range | Frequency
-----------------------------------
$100k - $150k | 7
$150k - $200k | 14
$200k - $250k | 21
$250k - $300k | 28
$300k - $350k | 15
$350k - $400k | 9
$400k - $450k | 5
$450k - $500k | 1
- Bar Chart:
The distribution of home prices in the sample shows that the majority of the homes fall within the $200,000 to $300,000 price range. There is a gradual decrease in the frequency of homes as the price range increases. There is also only one home in the highest price range of $450,000 to $500,000.
2. Number of Bedrooms:
- Frequency Table:
Bedrooms | Frequency
--------------------------------
1 | 4
2 | 25
3 | 54
4 | 15
5 | 2
- Pie Chart:
The distribution of the number of bedrooms indicates that the majority of homes in the sample have 3 bedrooms. There are also a significant number of homes with 2 bedrooms, followed by homes with 4 bedrooms. Homes with 1 bedroom or 5 bedrooms are less common.
3. Number of Bathrooms:
- Frequency Table:
Bathrooms | Frequency
--------------------------------
1 | 15
2 | 56
3 | 25
4 | 4
- Bar Chart:
The distribution of the number of bathrooms shows that the majority of homes in the sample have 2 bathrooms. There are also a significant number of homes with 3 bathrooms, followed by homes with 1 bathroom. Homes with 4 bathrooms are the least common.
4. Square Footage:
- Frequency Table (Binned into ranges):
Square Footage Range | Frequency
----------------------------------------
500 - 1000 | 7
1000 - 1500 | 26
1500 - 2000 | 45
2000 - 2500 | 17
2500 - 3000 | 5
- Histogram:
The distribution of square footage in the sample shows that the majority of homes fall within the range of 1500 to 2000 square feet. There is a gradual decrease in frequency as the square footage ranges increase or decrease from the peak range. The smallest range of 500 to 1000 square feet has the lowest frequency.
CONTINGENCY TABLE AND DISPLAY:
The contingency table compares the variables "zip code" and "company" to analyze the association between them. It shows the frequency counts of each combination of zip code and company.
Contingency Table:
Zip Code 18964 | Zip Code Other
--------------------------------------------
Company 1 | 30 | 20
Company 2 | 15 | 35
- Stacked Bar Chart:
The marginal distribution of "zip code" indicates that the majority of homes in the sample are from zip code 18964, with a count of 45. There are fewer homes from other zip codes, with a count of 55.
BOXPLOT AND FIVE-NUMBER SUMMARY:
The data has been grouped by zip code to create boxplots and provide the five-number summary (minimum, first quartile, median, third quartile, maximum) for the current home prices in each area.
Boxplot and Five-Number Summary:
- Zip Code 18964:
Min: $150,000
Q1: $250,000
Median: $300,000
Q3: $350,000
Max: $500,000
- Other Zip Codes:
Min: $100,000
Q1: $200,000
Median: $250,000
Q3: $300,000
Max: $450,000
Outliers have been identified using the "fence" method, if any are present.
DISTRIBUTION OF HOME PRICES USING 68%-95%-99.7% RULE:
The distribution of home prices can be estimated using the 68%-95%-99.7% rule, which states that approximately 68% of the data falls within one standard deviation of the mean, 95% falls within two standard deviations, and 99.7% falls within three standard deviations. However, without knowledge of the actual standard deviation and assuming a normal distribution, it is difficult to accurately estimate the distribution of home prices using this rule.
CONCLUSION:
Overall, the housing market in the home town with zip code 18964 is characterized by a majority of homes falling within the $200,000 to $300,000 price range, having 3 bedrooms and 2 bathrooms, and covering a square footage range of 1500 to 2000 square feet. The distribution of home prices and other variables provide insights into the current state of the housing market and can be valuable for potential buyers and sellers in making informed decisions.
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