1. Create a detailed flowchart, neatly drawn is fine or you can use software, of the process that you would use to completing a significant case study, report, or class project that was worth a significant proportion of you grade in a class (>25%). Did you learn anything or gain any insights as you created the flow chart?
2. Consider the following data compiled over several months from a foreman responsible for quality control from a company that installs home and commercial building exteriors of the errors/problems from installations, create a check sheet for this raw data.

miss cut panel	Open joint	Open joint	Open joint	miss cut panel	Bent trim
Open seam	Open seam	miss cut panel	Open seam	Miss cut trim	Open seam
Open joint	Panel Flaw	Miss cut trim	Miss cut trim	miss cut panel	Panel Flaw
miss cut panel	Bent trim	Exposed wrap	Bent trim	Open joint	miss cut panel
Panel Flaw	Contamination	Contamination	miss cut panel	Exposed wrap	Bent trim
Bent trim	Bent trim	Bent trim	miss cut panel	Contamination	miss cut panel
Open joint	miss cut panel	Miss cut trim	miss cut panel	Miss cut trim	Open joint
Open joint	Open joint	Open joint	Bent Trim	Open joint	miss cut panel
Miss cut trim	Open seam	Exposed wrap	Open seam	Panel Flaw	Miss cut trim
Miss cut trim	Miss cut trim	miss cut panel	miss cut panel	Panel Flaw	miss cut panel
Open seam	miss cut panel	miss cut panel	Open seam	Miss cut trim	Open seam
Open joint	Panel Flaw	Miss cut trim	Miss cut trim	miss cut panel	Panel Flaw
miss cut panel	Open seam	Exposed wrap	Open seam	Panel Flaw	Miss cut trim
Miss cut trim	Contamination	miss cut panel	miss cut panel	Open joint	miss cut panel

3. Using the data and check sheet from Question 2, create a Pareto Chart from the data. Based on your Pareto chart, which programs do you think that you should try to correct first, and why?

4. Consider the following data and first create a histogram of the data. Do you have any observations you would like to make about this data from the histogram?

0.49419	0.49839	0.50992	0.48939	0.49509	0.49119	0.49731	0.47782
0.48744	0.48954	0.50287	0.48671	0.49636	0.48704	0.48698	0.49289
0.50277	0.49298	0.49112	0.49130	0.50512	0.49882	0.50061	0.49989
0.49766	0.48216	0.50570	0.47826	0.50932	0.48107	0.51500	0.48556
0.49504	0.50010	0.51253	0.47786	0.49028	0.48196	0.50146	0.49641
0.50412	0.48901	0.50905	0.48488	0.50108	0.48455	0.49696	0.50062
0.51657	0.49007	0.49381	0.49210	0.50698	0.48643	0.51267	0.48484
0.50875	0.48476	0.50736	0.48159	0.50075	0.48882	0.50382	0.49520
0.49236	0.49669	0.51020	0.47730	0.50903	0.49718	0.50212	0.48465
0.49328	0.48803	0.48705	0.50047	0.50533	0.50188	0.51103	0.48085

5. Create a Cause and Effect (Ishikawa or Fishbone Diagram) for the program of not being able to find a specific file you saved on your laptop a year ago for a class project that you would like to refer to for a problem at work. After you create the diagram, are there an insights you gain to potentially avoid such a problem in the future?

6. Consider the following data, create a scatterplot for both GDP per capita and population and another for GDP per Capita and Population Density and then draw a conclusion about the relationship between the variables.

Entity	GDP per capita, PPP (constant 2017 international $)	Population density	Population (historical estimates)
Afghanistan	2058.4	54.596	35643420
Albania	12770.96	105.086	2879361
Algeria	11737.4	17.272	41136548
Argentina	23597.12	16.098	44054616
Armenia	12115.14	100.173	2851929
Australia	48398.55	3.197	24590336
Austria	54172.99	106.61	8797497
Azerbaijan	14121.41	121.852	10071569
Bangladesh	4160.703	1242.944	161793968
Brazil	14524.61	24.946	208504960
Cambodia	3928.374	89.682	15830694
Canada	48317.18	4.077	36554344
Chile	24470.7	24.704	18368582
China	14243.53	149.636	1410275968
Colombia	14171.32	43.58	48351668
Croatia	27154.08	74.085	4192468
Denmark	55356.68	143.432	5737286
Ecuador	11617.91	67.229	16696947
Egypt	11014.49	102.255	101789384
El Salvador	8454.052	302.445	6266661
Finland	47570.13	18.124	5508146
France	44577.07	117.146	64144092
Hungary	29501.12	107.264	9788940
Iceland	55638.49	3.408	343641
India	6182.922	455.469	1354195712
Indonesia	10935.63	140.877	264498848
Iran	14535.87	51.883	84505080
Mexico	19721.26	63.191	122839256
Nepal	3565.198	196.606	28183424
Netherlands	55088.63	511.054	17207204
New Zealand	42285.32	18.025	4746253
Nicaragua	6004.014	53.852	6480534
Nigeria	5190.356	212.453	193495904
Pakistan	4571.205	280.692	216379648
Poland	30064.5	125.854	38532816
Portugal	33044.71	112.521	10307528
Romania	27141.9	85.617	19698852
Russia	25926.44	8.882	145452544
Rwanda	1975.249	495.758	12230343
South Korea	40957.42	528.216	51511640
Spain	39528.93	93.242	46584172
Sweden	51947.95	24.694	10058191
Switzerland	69103.57	213.88	8451688
Tunisia	11234.49	76.026	11811441
Turkey	27913.82	106.661	82089824
United Kingdom	46372.39	273.074	66064808
United States	60109.66	36.053	329791232
Vietnam	7155.443	303.264	94033048
Zambia	3485.022	23.269	17298056
Zimbabwe	3795.642	38.131	14751101

7. Construct a set of X-bar and R-Charts for the following data and interpret the charts to see whether the process looks like it is in-control.

Sample #
1	5.026927	5.005555	4.95668	4.994999	5.026142
2	5.048867	5.052075	5.027222	4.993921	5.018301
3	4.944734	5.011558	5.010126	4.962489	5.022458
4	5.012786	5.037651	4.970024	4.958413	4.933708
5	4.990558	5.011921	5.011902	4.956729	4.990985
6	4.972817	4.979059	5.055553	4.961528	4.917318
7	5.024894	4.978343	4.958551	4.952427	5.003415
8	4.97988	4.945376	4.982025	5.010008	5.017826
9	4.928019	4.981581	4.919429	4.954324	5.000255
10	5.013187	5.021026	4.937678	4.944423	5.015729
11	5.10605	4.96354	4.955739	5.059814	5.009434
12	5.034777	4.955624	4.949033	5.053548	4.951553
13	5.030386	4.991413	4.978321	5.110369	5.037815
14	5.068179	4.973174	5.001058	4.910348	5.041896
15	4.963863	5.050507	4.978714	5.076796	5.041754
16	4.999933	5.017094	5.00387	5.036427	4.971726
17	5.021264	4.993136	4.97147	5.051446	4.968699
18	4.991311	4.93365	4.96019	5.036548	5.106264
19	4.961819	4.983278	4.902357	5.012143	4.992442
20	5.002846	5.044409	4.969796	4.961295	5.004543

 

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