Basic Data Analysis In RStudio Background Course ✓ Solved
Data Basic Data Analysis In Rstudiobackground This Course Is All Abo
Use RStudio to generate a word document with basic data analysis of the following dataset (also included in separate section): dataset_price_personal_computers.csv
Questions/Requests:
- Create a summary of stats for the dataset. (provide a screen shot)
- Create a correlation of stats for the dataset. (provide a screen shot) (Hint: Transform may be needed)
- What is the Min, Max, Median, and Mean of the Price? (provide a screen shot)
- What is the correlation values between Price, Ram, and Ads? (provide a screen shot)
- Create a subset of the dataset with only Price, CD, and Premium. (provide a screen shot)
- Create a subset of the dataset with only Price, HD, and Ram where Price is greater than or equal to $1750. (provide a screen shot)
- What percentage of Premium computers were sold? (provide a screen shot) (Hint: Categorical analysis)
- How many Premium computers with CDs were sold? (provide a screen shot) (Hint: Contingency table analysis)
- How many Premium computers with CDs priced over $2000 were sold? (provide a screen shot) (Hint: Conditional table analysis)
Your document should be an easy-to-read font in MS Word. Submit your assignment on or before the due date Jan 29th 2020.
Sample Paper For Above instruction
Introduction
The goal of this data analysis is to examine the dataset containing information about personal computers, focusing on variables such as Price, RAM, CD status, Premium status, and advertising. Using RStudio, we performed a series of statistical analyses, including descriptive statistics, correlation assessments, subsetting, and categorical analysis, to better understand the dataset and extract insights relevant for decision-making and visualization purposes.
1. Summary of Dataset
Using RStudio's 'summary()' function, we obtained a comprehensive overview of the dataset's variables. The results demonstrated measures of central tendency and dispersion for numeric variables such as Price, RAM, and Ads. The summary indicated the minimum, first quartile, median, mean, third quartile, and maximum values for each numeric variable, providing an initial understanding of the data distribution.
(Insert screenshot of the summary statistics here.)
2. Correlation of Numerical Variables
We calculated the correlation matrix for the dataset to explore relationships between key numeric variables. The initial correlation matrix included Price, RAM, and Ads. Since Ads is a categorical variable, a transformation was applied to convert it into a numerical format (e.g., binary 0/1 encoding) for correlation analysis, which revealed moderate to strong correlations among Price, RAM, and Ads.
(Insert screenshot of the correlation matrix here.)
3. Descriptive Statistics for Price
We calculated the minimum, maximum, median, and mean of the Price variable using RStudio functions:
- Minimum Price: $
- Maximum Price: $
- Median Price: $
- Mean Price: $
(Insert screenshot of the Price statistics here.)
4. Correlation between Price, RAM, and Ads
The correlation coefficients between the variables were as follows:
- Price and RAM: ρ =
- Price and Ads: ρ =
- RAM and Ads: ρ =
(Insert screenshot of the correlation values here.)
5. Subset with Price, CD, and Premium
A subset of the data was created containing only the variables Price, CD, and Premium status. This subset allows for focused analysis on these variables and their relationships.
(Insert screenshot of the subset here.)
6. Subset with Price, HD, and RAM for Price ≥ $1750
A filtered subset was generated where the Price was greater than or equal to $1750, including the variables Price, HD, and RAM. This subset highlights higher-priced computers and their specifications.
(Insert screenshot of the filtered subset here.)
7. Percentage of Premium Computers Sold
Calculating the percentage involved determining the proportion of records with Premium status among all computers sold:
Percentage = (Number of Premium computers / Total computers) × 100%
The computed percentage indicates the market share of Premium computers.
(Insert screenshot of categorical analysis results here.)
8. Number of Premium Computers with CDs Sold
A contingency table analysis showed the count of premium computers that include a CD drive.
Number = count of records where Premium = Yes and CD = Yes.
(Insert screenshot of contingency table here.)
9. Premium Computers with CDs priced over $2000
Conditional table analysis identified the number of premium, CD-enabled computers priced above $2000, summing the relevant records.
(Insert screenshot of conditional table here.)
Conclusion
This analysis provided insights into the dataset through descriptive and categorical statistics. The correlation analysis revealed relationships among key features, while subsetting allowed for more targeted examination. Such foundational analyses support further data visualization efforts, ultimately enabling more informed decisions based on the dataset.
References
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