QNT 561: Descriptive Statistics and Interpretation

Descriptive Statistics and Interpretation

QNT/561

August 4, 2014

Matthew Radio

Descriptive Statistics and Interpretation

After collecting the data for Tarlich Supermarket, the next step was to use statistics to describe, analyze, and interpret the data. For the study, the independent variable is the amount of produce inventory ordered, and the dependent variable is the loss due to spoilage. The research question for the study asks if the percentage of food thrown out, at Tarlich Supermarket, due to spoilage is higher than the industry average.

Data Collection and Descriptive Statistics

Appendix A shows the raw data collected and the calculated percentage of food thrown away. The sample was chosen by recording every third shipment of perishable foods, which came in every two days. Using the percentage of food thrown away, histograms were created to assess the distribution; refer to Appendix B. Since the data is normally distributed , the appropriate descriptive statistics to use are the mean and standard deviation. Calculations for the descriptive statistics can be found in Appendix C.

Percentage of Perishable Food Thrown Out

The perishable foods in each shipment were divided into three categories before the data was recorded. The descriptive statistics shows that an average of 9.5 percent of fruits and vegetables, 6.4 percent of meat and poultry, and 12.9 percent of seafood in each shipment is thrown out.

Descriptive Statistics Interpretation

One hundred shipments were randomly selected and their perishable food content for each of three groups recorded, in pounds. The number of pounds later thrown out per shipment was also recorded, and the percentage of perishables thrown out calculated per group.

It was found that 8.2 to 11.3 percent of fruits and vegetables, 5.0 to 7.3 percent of meat and poultry, and 9.8 to 15.6 percent of seafood spoil before being sold. The average percent of food thrown away was 9.5 percent for fruits and vegetables, 6.4 percent for meat and poultry, and 12.9 percent for seafood, with a standard deviation of 1.0, 0.6, and 1.6 percent, respectively. There is 90% confidence that the population percentage of spoiled food average is between 9.4 and 9.7 percent for fruits and vegetables, 6.3 and 6.5 percent for meat and poultry, and 12.6 and 13.1 percent for seafood.

Conclusion

Using the sampling and data collection plan, Tarlich was able to collect information for the sample of shipments needed. Once the information was gathered and divided into the determined groups, Tarlich performes descriptive statistics on the data. Interpretation of the descriptive statistics has helped Tarlich supermarket calculate what the spoil rate for their different perishables are. The research study will continue on to determine a course of action for the store.

Appendix A: Raw Data

Appendix A: Raw Data Continued

Day

sample

taken

Fruits And

Vegetables

Meat and

Poultry

Seafood

Fruits And

Vegetables

Meat and

Poultry

Seafood

Fruits And

Vegetables

Meat and

Poultry

Seafood

mon1801808017.211.210.29.6%6.2%12.8%

sun1901909016.49.812.38.6%5.2%13.7%

sat20020010020.312.311.510.2%6.2%11.5%

fri

20020010016.513.212.28.3%6.6%12.2%

thurs1901909018.411.59.89.7%6.1%10.9%

wed1801808019.712.610.910.9%7.0%13.6%

tues1801808019.612.012.510.9%6.7%15.6%

mon1801808020.111.910.411.2%6.6%13.0%

sun1901909017.912.311.79.4%6.5%13.0%

sat20020010016.512.99.98.3%6.5%9.9%

fri20020010016.411.410.88.2%5.7%10.8%

thurs1901909020.39.911.510.7%5.2%12.8%

wed1801808016.513.112.29.2%7.3%15.3%

tues1801808019.612.712.210.9%7.1%15.3%

mon1801808020.111.69.811.2%6.4%12.3%

sun1901909017.99.810.99.4%5.2%12.1%

sat20020010017.912.312.59.0%6.2%12.5%

fri20020010016.512.910.98.3%6.5%10.9%

thurs1901909016.411.412.58.6%6.0%13.9%

wed1801808017.29.910.49.6%5.5%13.0%

tues1801808016.413.111.79.1%7.3%14.6%

mon1801808020.311.99.911.3%6.6%12.4%

sun1901909016.512.310.88.7%6.5%12.0%

sat20020010019.712.912.39.9%6.5%12.3%

fri20020010019.612.311.59.8%6.2%11.5%

thurs1901909020.112.912.210.6%6.8%13.6%

wed1801808017.911.412.59.9%6.3%15.6%

tues1801808016.59.910.49.2%5.5%13.0%

mon1801808016.413.111.79.1%7.3%14.6%

sun1901909020.312.79.910.7%6.7%11.0%

sat20020010020.311.610.810.2%5.8%10.8%

fri20020010016.512.311.58.3%6.2%11.5%

thurs1901909019.713.212.210.4%6.9%13.6%

wed1801808019.611.512.210.9%6.4%15.3%

tues1801808016.512.610.49.2%7.0%13.0%

mon1801808016.412.011.79.1%6.7%14.6%

sun1901909017.211.99.99.1%6.3%11.0%

sat20020010016.412.310.88.2%6.2%10.8%

fri20020010020.312.912.310.2%6.5%12.3%

thurs1901909016.511.411.58.7%6.0%12.8%

wed1801808016.59.912.29.2%5.5%15.3%

tues1801808019.713.112.510.9%7.3%15.6%

mon1801808019.613.110.410.9%7.3%13.0%

sun1901909016.512.711.78.7%6.7%13.0%

sat20020010016.411.69.98.2%5.8%9.9%

fri20020010017.212.310.88.6%6.2%10.8%

thurs1901909016.512.011.58.7%6.3%12.8%

wed1801808016.511.912.29.2%6.6%15.3%

tues1801808019.712.312.210.9%6.8%15.3%

mon1801808020.312.910.411.3%7.2%13.0%

sun1901909016.511.411.78.7%6.0%13.0%

sat20020010019.79.99.99.9%5.0%9.9%

fri20020010019.612.710.89.8%6.4%10.8%

thurs1901909020.111.612.310.6%6.1%13.7%

wed1801808019.712.310.810.9%6.8%13.5%

tues1801808020.312.011.511.3%6.7%14.4%

mon1801808016.511.912.29.2%6.6%15.3%

sun1901909016.412.312.28.6%6.5%13.6%

sat20020010017.212.39.88.6%6.2%9.8%

fri20020010016.512.910.98.3%6.5%10.9%

thurs1901909016.511.412.58.7%6.0%13.9%

wed1801808019.79.912.210.9%5.5%15.3%

tues1801808020.312.710.411.3%7.1%13.0%

mon1801808020.111.611.711.2%6.4%14.6%

sun1901909019.712.310.910.4%6.5%12.1%

sat20020010020.311.612.510.2%5.8%12.5%

fri20020010016.512.312.28.3%6.2%12.2%

thurs1901909016.412.010.48.6%6.3%11.6%

wed1801808017.211.912.29.6%6.6%15.3%

tues1801808016.512.310.49.2%6.8%13.0%

mon1801808017.212.311.79.6%6.8%14.6%

sun1901909016.512.99.98.7%6.8%11.0%

sat20020010016.511.410.88.3%5.7%10.8%

fri20020010019.79.912.39.9%5.0%12.3%

thurs1901909020.312.710.810.7%6.7%12.0%

wed1801808016.512.99.89.2%7.2%12.3%

tues1801808016.411.410.99.1%6.3%13.6%

mon1801808017.29.912.59.6%5.5%15.6%

sun1901909016.513.112.28.7%6.9%13.6%

sat20020010017.212.710.48.6%6.4%10.4%

fri20020010016.511.612.28.3%5.8%12.2%

thurs1901909016.512.310.48.7%6.5%11.6%

wed1801808019.713.211.710.9%7.3%14.6%

tues1801808020.312.39.911.3%6.8%12.4%

mon1801808016.512.310.89.2%6.8%13.5%

sun1901909016.412.912.38.6%6.8%13.7%

sat20020010016.511.410.88.3%5.7%10.8%

fri20020010016.49.912.28.2%5.0%12.2%

thurs1901909017.212.710.49.1%6.7%11.6%

wed1801808016.512.911.79.2%7.2%14.6%

tues1801808017.211.49.99.6%6.3%12.4%

mon1801808016.59.910.89.2%5.5%13.5%

sun1901909016.513.112.38.7%6.9%13.7%

sat20020010019.712.310.89.9%6.2%10.8%

fri20020010020.312.912.210.2%6.5%12.2%

thurs1901909016.511.410.48.7%6.0%11.6%

wed1801808016.59.911.79.2%5.5%14.6%

tues1801808019.712.710.810.9%7.1%13.5%

mon1801808020.311.612.311.3%6.4%15.4%

sun1901909016.512.310.88.7%6.5%12.0%

Weight (lb) arrived in shipment

Weight (lb) thrown away due to

spoilage

Percentage thrown away

Appendix B: Histograms

Day

sample

taken

Fruits And

Vegetables

Meat and

Poultry

Seafood

Fruits And

Vegetables

Meat and

Poultry

Seafood

Fruits And

Vegetables

Meat and

Poultry

Seafood

mon1801808017.211.210.29.6%6.2%12.8%

sun1901909016.49.812.38.6%5.2%13.7%

sat20020010020.312.311.510.2%6.2%11.5%

fri

20020010016.513.212.28.3%6.6%12.2%

thurs1901909018.411.59.89.7%6.1%10.9%

wed1801808019.712.610.910.9%7.0%13.6%

tues1801808019.612.012.510.9%6.7%15.6%

mon1801808020.111.910.411.2%6.6%13.0%

sun1901909017.912.311.79.4%6.5%13.0%

sat20020010016.512.99.98.3%6.5%9.9%

fri20020010016.411.410.88.2%5.7%10.8%

thurs1901909020.39.911.510.7%5.2%12.8%

wed1801808016.513.112.29.2%7.3%15.3%

tues1801808019.612.712.210.9%7.1%15.3%

mon1801808020.111.69.811.2%6.4%12.3%

sun1901909017.99.810.99.4%5.2%12.1%

sat20020010017.912.312.59.0%6.2%12.5%

fri20020010016.512.910.98.3%6.5%10.9%

thurs1901909016.411.412.58.6%6.0%13.9%

wed1801808017.29.910.49.6%5.5%13.0%

tues1801808016.413.111.79.1%7.3%14.6%

mon1801808020.311.99.911.3%6.6%12.4%

sun1901909016.512.310.88.7%6.5%12.0%

sat20020010019.712.912.39.9%6.5%12.3%

fri20020010019.612.311.59.8%6.2%11.5%

thurs1901909020.112.912.210.6%6.8%13.6%

wed1801808017.911.412.59.9%6.3%15.6%

tues1801808016.59.910.49.2%5.5%13.0%

mon1801808016.413.111.79.1%7.3%14.6%

sun1901909020.312.79.910.7%6.7%11.0%

sat20020010020.311.610.810.2%5.8%10.8%

fri20020010016.512.311.58.3%6.2%11.5%

thurs1901909019.713.212.210.4%6.9%13.6%

wed1801808019.611.512.210.9%6.4%15.3%

tues1801808016.512.610.49.2%7.0%13.0%

mon1801808016.412.011.79.1%6.7%14.6%

sun1901909017.211.99.99.1%6.3%11.0%

sat20020010016.412.310.88.2%6.2%10.8%

fri20020010020.312.912.310.2%6.5%12.3%

thurs1901909016.511.411.58.7%6.0%12.8%

wed1801808016.59.912.29.2%5.5%15.3%

tues1801808019.713.112.510.9%7.3%15.6%

mon1801808019.613.110.410.9%7.3%13.0%

sun1901909016.512.711.78.7%6.7%13.0%

sat20020010016.411.69.98.2%5.8%9.9%

fri20020010017.212.310.88.6%6.2%10.8%

thurs1901909016.512.011.58.7%6.3%12.8%

wed1801808016.511.912.29.2%6.6%15.3%

tues1801808019.712.312.210.9%6.8%15.3%

mon1801808020.312.910.411.3%7.2%13.0%

sun1901909016.511.411.78.7%6.0%13.0%

sat20020010019.79.99.99.9%5.0%9.9%

fri20020010019.612.710.89.8%6.4%10.8%

thurs1901909020.111.612.310.6%6.1%13.7%

wed1801808019.712.310.810.9%6.8%13.5%

tues1801808020.312.011.511.3%6.7%14.4%

mon1801808016.511.912.29.2%6.6%15.3%

sun1901909016.412.312.28.6%6.5%13.6%

sat20020010017.212.39.88.6%6.2%9.8%

fri20020010016.512.910.98.3%6.5%10.9%

thurs1901909016.511.412.58.7%6.0%13.9%

wed1801808019.79.912.210.9%5.5%15.3%

tues1801808020.312.710.411.3%7.1%13.0%

mon1801808020.111.611.711.2%6.4%14.6%

sun1901909019.712.310.910.4%6.5%12.1%

sat20020010020.311.612.510.2%5.8%12.5%

fri20020010016.512.312.28.3%6.2%12.2%

thurs1901909016.412.010.48.6%6.3%11.6%

wed1801808017.211.912.29.6%6.6%15.3%

tues1801808016.512.310.49.2%6.8%13.0%

mon1801808017.212.311.79.6%6.8%14.6%

sun1901909016.512.99.98.7%6.8%11.0%

sat20020010016.511.410.88.3%5.7%10.8%

fri20020010019.79.912.39.9%5.0%12.3%

thurs1901909020.312.710.810.7%6.7%12.0%

wed1801808016.512.99.89.2%7.2%12.3%

tues1801808016.411.410.99.1%6.3%13.6%

mon1801808017.29.912.59.6%5.5%15.6%

sun1901909016.513.112.28.7%6.9%13.6%

sat20020010017.212.710.48.6%6.4%10.4%

fri20020010016.511.612.28.3%5.8%12.2%

thurs1901909016.512.310.48.7%6.5%11.6%

wed1801808019.713.211.710.9%7.3%14.6%

tues1801808020.312.39.911.3%6.8%12.4%

mon1801808016.512.310.89.2%6.8%13.5%

sun1901909016.412.912.38.6%6.8%13.7%

sat20020010016.511.410.88.3%5.7%10.8%

fri20020010016.49.912.28.2%5.0%12.2%

thurs1901909017.212.710.49.1%6.7%11.6%

wed1801808016.512.911.79.2%7.2%14.6%

tues1801808017.211.49.99.6%6.3%12.4%

mon1801808016.59.910.89.2%5.5%13.5%

sun1901909016.513.112.38.7%6.9%13.7%

sat20020010019.712.310.89.9%6.2%10.8%

fri20020010020.312.912.210.2%6.5%12.2%

thurs1901909016.511.410.48.7%6.0%11.6%

wed1801808016.59.911.79.2%5.5%14.6%

tues1801808019.712.710.810.9%7.1%13.5%

mon1801808020.311.612.311.3%6.4%15.4%

sun1901909016.512.310.88.7%6.5%12.0%

Weight (lb) arrived in shipment

Weight (lb) thrown away due to

spoilage

Percentage thrown away

Appendix C: Descriptive Statistics

Percentage of Fruits and Vegetables Thrown Away Due to Spoilage

Central Tendency: Mean = 9.5%

Dispersion: Standard Deviation = 1.0%

Number: 100

Min/Max: 8.2% and 11.3%

Confidence Interval: 9.4% to 9.7%

Percentage of Meat and Poultry Thrown Away Due to Spoilage

Central Tendency: Mean = 6.4%

Dispersion: Standard Deviation = 0.6%

Number: 100

Min/Max: 5.0% and 7.3%

Confidence Interval: 6.3% to 6.5%

Percentage of Seafood Thrown Away Due to Spoilage

Central Tendency: Mean = 12.9%

Dispersion: Standard Deviation = 1.6%

Number: 100

Min/Max: 9.8% and 15.6%

Confidence Interval: 12.6% to 13.1%

Content and Development 4 Points	Points Earned 3.8/4
	Additional Comments:
All key elements of the assignment are covered in a substantive way, including: · Excel Spreadsheet was created. · Variables are listed. · Descriptive stats provided · Applicable charts/graphs displayed.. · Interpretation of statistics given.	Good job. See comments above.
Readability, Style, and Mechanics 1 Point	Points Earned .95 /1
	Additional Comments:
Sentences are complete, clear, and concise. Rules of grammar are followed.	See correct format for figures and tables in Center for Writing Excellence. (Title, labels, location etc)
The paper, including the title page, reference page, tables, and appendixes, follows APA formatting guidelines, including effective use of style.
The paper is no more than 700 words.
Total 5 Points	Points Earned 4.75/5
Overall Comments:

�Not yet, really. This is inferential statistics.

�Do you want to consider a two-tailed test? It would be good for Tarlich if they were lower, right?

�No! Why do you say this?

Normality is quite an assumption.

Generally to determine normality you would have to look at a frequency histogram. You would divide the variable pounds into intervals of say 100. How many shipments were between 24 and 25 hundred pounds? How may were between 25 and 26? 26 and 27? Etc.

Then you plot a frequency distribution . If it is bell shaped, then the data is approximately normal.

�A question to consider as a team is whether this division of food types should give way to 3 separate research questions.

Generally, stratified sampling is used to make sure each subgroup is represented in one population. The population parameter applies to all the subgroups. Here it seems that the various food groups should and do have different shelf lives. Is it fair to lump them into one percentage that describes all perishable items?

Your call. You could argue either way.

�None of these “bar graphs” are bell shaped.