StackExchange Data Analysis

Data Source:

This dataset was queried from stackexchange.com.

It consists of two different csv files.

• One containing the questions posts
• Another containing the answer posts

Contributors:

This project was worked upon by the following 4 members together as a team:

• Siddharth Suresh
• Sneha Choudhary
• Suchetha Sharma
• Vidhi Gupta

Context:

The intent of the project was to use regression modeling to:

1. Determine the parameters that contributed to a higher probability of getting an accepted answer for a question
2. Predict the score of a posted Answer

Conclusions from the analysis:

1. Determine the parameters that contributed to a higher probability of getting an accepted answer for a question

• Increase in Score, ViewCount, PostLength_Words, InactiveSince_Days increases the odds of getting an accepted answer.
• Increase in AnswerCount, CommentCount and MeanAnswerTime_Days decreases the odds of getting an accepted answer.
• If a question is ever marked favorite, it increases the odds of getting an accepted answer.
• Questions belonging to , and tag have higher odds of getting an accepted answer.
• Questions belonging to and have lower odds of getting an accepted answer.

2. Predicting the score of a posted Answer

The entire Dataset was split into Training (70%) and Testing (30%) Dataframe. Min-Max accuracy method was implemented which is the average between the minimum and the maximum prediction of the model.

The result achieved was 91.6% implying that the model is statistically significant.