Reference no: EM132255617

Statistical Data Management Assignment -

Background: Suppose we were going to do a statistical analysis of the University of Illinois football team's record and how it impacts their AP ranking and Bowl game results. To do so, we would need a data set that's fully validated and cleaned.

Dataset: You will work with a data set containing information from the 127 seasons of University of Illinois football. The raw data set illinifb18.dat contains data from 1892 to 2018.

Field	Description	Notes
1	Obs	Observation number
2	Season
3	Conf	Conference
4	W	Wins
5	L	Losses
6	T	Ties
7	Pct	Win percentage
8	SRS	Simple Rating System: A rating that takes into account average point differential and strength of schedule. Average of all teams in a season is 0.
9	SOS	Strength of Schedule: Average of all teams in a season is 0.
10	AP_pre	Rank in pre-season AP poll. Possible values are 1-25 and missing if unranked.
11	AP_high	Highest rank of the team in the AP poll during that season. Possible values are 1-25 and missing if unranked.
12	AP_post	Rank in final AP poll at the end of the season. Possible values are 1-25 and missing if unranked.
13	ConfTitle	Did Illinois win its Conference Title: Y or N
14	Coach	Head coach (or coaches)
15	Record	Team record
16	Bowl	Name of post-season bowl game played in, or missing
17	BowlResult	Result of Bowl game: W or L

Goal: Adequately prepare this dataset for statistical analysis. Here is a list of items you may need to consider.

• Reading raw data files.
• Creating formats and labels.
• Deriving new variables via calculations or recoding.
• Subsetting data.
• Checking data for errors.
• Validating and cleaning data.

To help you along, here are some data details.

• Each record is a unique season, so each value of Season must be unique.
• The values of W, L, T, and Pct should coincide correctly. Winning percentage is equal to the number of wins (W) divided by the total number of games (W+L+T).
• No one is expected to know the proper spelling of each Head Coach's name. If there are any typos in a coach's name, each unique spelling would appear in a frequency report.
• In some years, Illinois switched their head coach in the middle of the season. If more than one coach is listed for a season, clean the Coach variable to note which coach had the most wins that season.
• In some years, Illinois had more than one person simultaneously filling the role of head coach. If no coach is listed, it means that more than one person shared the duties of coach. Learn who they were by searching the internet and clean the Coach variable to contain the name of the coach whose last name comes first in alphabetical order.
• Clean the Record variable to match the W, L, and T entries.

Midterm Report: A summary report that includes the following -

1. Title of the project.

2. Your name.

3. Methods section:

• Description of the original data file including what type of input style it uses.
• Description of the guidelines used to validate the data.
• Description of the issues needed to be cleaned and how it will was done (though not needing to explain the programming code specifically).
• Description of additional data preparation that you performed.
• Description of variables to be analyzed including attributes such as name and type.

You do not have to list all the variables in the original sourced file, but do mention the ones you bring to SAS for the creation of the SAS data set.

4. Results section:

• Tables and visualizations pertaining to validation and cleaning.
• Write-up of the results. Point out notable information from the charts and tables.

5. To verify that the cleaning was thoroughly completed, also answer these questions in your Results section:

a. Identify which Head Coach or Coaches had the most wins in his career with the University of Illinois football team.

b. Identify which Season(s) saw the football team with their highest ranking for the university across all seasons. Note that #1 is the highest ranking possible.

c. Identify the number of times that Illinois won its conference title.

d. Identify which decade had the most wins in a decade. For example, 1892-1899 will be the decade known as the 1890s; 1900-1909 is the 1900s; ... 2010-2019 is the 2010s.

6. Write in complete sentences and pay attention to grammar, spelling, readability and presentation. If you include a table or chart, make sure you say something about it. If you're not discussing a result, then it doesn't belong in your report.

In terms of length, it probably shouldn't take more than 2-3 pages to explain your work on this dataset. That does not include the space occupied by tables and other output. If you have a point to make, get to it. If you find yourself writing things simply for the sake of padding the word-count, you're writing the wrong things.

You must complete the exercises and turn in the SAS program file and Report just like with HW. Submissions must be uploaded to our Compass 2g site on the Midterm page.

Attachment:- Assignment Files.rar