need help with Data collection and Results

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Mathematics

Morgan State University

Description

1. Statement of the problem: Describe the questions you address and any key issues surrounding the questions.

2. Data collection: Explain how you collect data. Include any questions you asked. Also, include response rates.

3. Analyses: Describe the analyses you did. Be ready to explain why you believe these methods are justified.

4. Results: Present relevant descriptive statistics. Include tables or graphs that support your analyses.


more explanation:

my topic : I lean towards. What is your major? then I did something related. I study to see if there is any correlation between time spent in the lab per week to grade point average. it gives us a lot of variables to compare like major, classification, how many years that person has been in college

how I collect data: I talked to as many students as possible at university.




Unformatted Attachment Preview

Final Project Questionnaire Major Classification # of year enrolled G.P.A Hours per week spent in lab Gender EEGR Junior 6 2.50 4 Female EEGR Junior 4 3.00 4 Male EEGR Sophomore 4 2.00 2 Male EEGR Junior 5 2.20 3 Male EEGR Junior 4 2.00 3 Male EEGR Junior 4 2.25 2 Male EEGR Junior 5 2.70 4 Male EEGR Sophomore 2 3.20 6 Female CEGR Junior 3 3.63 2 Male CEGR Junior 3 2.60 3 Male CEGR Junior 3 3.24 0 Male CEGR Junior 3 2.50 2 Male CEGR Senior 3 3.00 5 Male CEGR Junior 3 3.24 2 Male CEGR Sophomore 2 3.55 0 Male CEGR Junior 3 2.24 2 Male CEGR Sophomore 2 3.00 3 Male CEGR Junior 3 2.77 2 Male CEGR Senior 4 3.50 6 Male Major Classification # of year enrolled G.P.A Hours per week spent in lab Gender EEGR Senior 4 3.80 9 Male EEGR Senior 4 3.80 2 Male EEGR Senior 5 3.10 4 Male EEGR Junior 3 3.90 6 Female EEGR Senior 4 3.01 2 Male EEGR Senior 4 3.00 4 Male IEGR Senior 3 2.90 5 Male EEGR Senior 4 3.02 9 Male EEGR Senior 4 3.20 6 Male EEGR Sophomore 2 3.30 4 Female EEGR Junior 4 2.80 2 Male EEGR Sophomore 2 3.20 4 Male EEGR Junior 3 2.50 3 Male EEGR Freshmen 1 2.70 3 Male EEGR Junior 4 2.70 0 Male EEGR Junior 3 3.14 10 Male EEGR Senior 4 3.50 7 Male EEGR Junior 4 3.60 9 Female EEGR Senior 6 2.60 0 Female Major Classification # of year enrolled G.P.A Hours per week spent in lab Gender EEGR Senior 4 3.20 10 Male EEGR Senior 3 3.40 10 Female CEGR Freshmen 1 3.00 4 Female IEGR Sophomore 2 2.95 3 Male EEGR Junior 4 3.32 6 Male IEGR Senior 5 3.70 10 Male IEGR Sophomore 2 3.00 4 Female CEGR Junior 4 3.33 7 Male CEGR Sophomore 2 2.75 2 Male EEGR Freshmen 1 2.50 1 Male EEGR Junior 3 3.45 5 Male IEGR Junior 3 3.20 0 Female EEGR Senior 4 3.65 4 Female CEGR Freshmen 1 3.13 3 Male EEGR Sophomore 2 2.50 1 Male EEGR Freshmen 1 2.75 1 Male CEGR Senior 6 3.0 5 Male EEGR Junior 3 3.32 4 Female IEGR Junior 3 3.90 7 Female Morgan State University (Final Project title) Lab Date Submitted:________TBA___________ Introduction: Utilizing core concepts in probability and statistics students were asked to conduct a study based on a range of topics not limited to engineering, economics, sports, psychology etc. The goal of this data analysis project is for groups of three- four student to synthesize all material learned from this course and apply it to real world applications. Statistical techniques such as hypothesis testing, confidence intervals, normality testing, etc. are utilized to collect data and assert a wellresearched and tested study. Problem Statement: Morgan State University is the largest historically black university/college in the state of maryland, founded in 1867. According to the Middle States Commission on Higher Education the institution ranking #1 in producing engineering degrees awarded to africanamericans in maryland. Specifically Morgan State University also ranks #1 in producing the most amount of african-americans majoring in civil, electrical and industrial engineering in the state of maryland. This prompted our team to conduct a study into the success of this institution. A study was conducted amongst science, technology, engineering and mathematics majors to detect a correlation between time spent in the various laboratories located in the institution to grade point average. We hypothesize that the more time spent per week in laboratories has a positive correlation to grade point average amongst students pursuing technical degrees. Data collection: Analyses: The data collection from the survey was compiled into SAS university edition to be analyzed. Initially several variables including area of study, hours spent per week in laboratories, grade point average, etc. were compiled into a data matrix for various functions to pull from. Hypothesis testing was then conducted, in order to determine a feasible experiment our team first conducted this test to establish statistical significant. Our null hypothesis stating students who spend equal or greater to four hours in the laboratories per week have an average g.p.a above a 3.0 on a 4.0 scale. While the alternative state being the number of hours spent in labs per week has no correlation to grade point average. Once this testing was done, we analysed the patterns of the data collected, a mean, variance and standard deviation was calculated. In addition the data was plotted. By employing these techniques not only were we able to determine the average amount of hours spent compared to grade point average, but also plot a correlation associated with the data. In addition normal distribution was found, in order to represent the distribution of random variables as a graph. Normality tests are utilized to determine if a data set is well-modeled by its normal distribution, after determining the normal distribution our group conducted this test to compute how likely a random variable is distributed throughout the data set. To solidify our hypothesis a confidence interval was found, to identity the probability of achieving a range of grade point averages within a defined amount of hours spent in the labs per week. Utilizing all these techniques we believe it displays sufficient enough data to support our hypothesis.
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