Use the “Project 2 Data Schools file to complete the following:
1. Using the data in the Property Values Data sheet, produce a scatter plot with the passing rate as the response variable and the ‘Average Property Values in the District’ as the explanatory variable. Print as page 3.
2. Repeat Step 2. using the ‘Welfare Rate’ as the explanatory variable in the Welfare Rate Data sheet. Print as page 4.
3. Repeat Step 2. using the ‘Average Daily Attendance Rate’ as the explanatory variable in the Attendance Data sheet. Print as page 5.
4. Run a simple regression with the passing rate as the response variable and ‘Average Property Values in the District’ as the explanatory variable.
On the Results sheet :
Indicate the correlation coefficient (R)
Interpret the coefficient of determination (R²)
Interpret the significance
Give the linear regression equation
Use the regression equation to predict one passing rate value.
Note: These can be written by hand on the printouts, or typed into the sheet before printing. Print this as page 6.
5. Run a simple regression with the passing rate as the response variable and ‘Welfare Rate’ as the explanatory variable.
On the Results sheet :
Indicate the correlation coefficient (R)
Interpret the coefficient of determination (R²)
Interpret the significance
Give the linear regression equation
Use the regression equation to predict one passing rate value.
Note: These can be written by hand on the printouts, or typed into the sheet before printing. Print this as page 7.
6. Run a simple regression with the passing rate as the response variable and ‘Average Daily Attendance Rate’ as the explanatory variable.
On the Results sheet :
Indicate the correlation coefficient (R)
Interpret the coefficient of determination (R²)
Interpret the significance
Give the linear regression equation
Use the regression equation to predict one passing rate value.
Note: These can be written by hand on the printouts, or typed into the sheet before printing. Print this as page 8.
Schools Property Passing
X3 Y
Bluffton 62678 85
Shawnee 130910 73
Spencerville 51645 68
Delphos 88453 65
Elida 65550 62
Northeastern 88789 72
Ayersville 82707 68
Defiance 56333 63
Hicksville 56411 59
Central 53923 56
Berlin-Milan 76878 77
Perkins 117545 74
Huron 105588 74
Margaretta 74601 66
Sandusky 72425 37
Pettisville 53948 78
Wauseon 60896 75
Evergreen 69432 72
Archbold-Area 107547 69
Pike-Delta-York 48638 66
Gorham-Fayette 57221 51
Swanton 69320 50
Arlington 55478 84
Vanlue 49606 83
Liberty-Benton 77503 78
Van Buren 151992 75
Cory-Rawson 69242 73
Arcadia 78102 64
McComb 69347 61
Findlay 92648 60
Ada 52655 69
Kenton 61155 54
Liberty Center 57685 82
Patrick Henry 63134 75
Napoleon Area 84245 73
Holgate 49709 71
Monroeville 63103 64
Bellevue 66912 55
Willard 58832 53
Norwalk 72266 50
Anthony Wayne 88004 75
Sylvania 101503 72
Maumee 117921 69
Oregon 123599 52
Washington 102485 51
Springfield 98346 49
Benton Carroll Salem 237206 81
Danbury 182360 65
Genoa 53120 65
Port Clinton 129961 50
Paulding 46163 59
Columbus Grove 55568 84
Kalida 44267 81
Continental 37277 79
Ottawa-glandorf 64288 77
Pandora-Gilboa 55446 67
Leipsic 62648 47
Gibsonburg 46098 71
Lakota 55933 66
Fremont 74874 57
Woodmore 90484 56
Clyde-Green Springs 55724 47
Bettsville 37269 83
Seneca East 50895 80
Old Fort 50712 78
Hopewell-Loudon 72201 74
New Riegel 41376 73
Tiffin 65291 67
Fostoria 62268 34
Van Wert 67932 61
Edon-Northwest 38462 73
Milcreek-West Unity 40239 71
Bryan 81152 69
North Central 59396 68
Montpelier 44383 67
Edgerton 54040 61
Stryker 65532 47
Perrysburg 97888 98
Elmwood 47644 68
Bowling Green 84682 68
Otsego 57601 64
Northwood 77077 61
Eastwood 67929 60
Lake 95859 55
Rossford 123725 54
North Baltimore 58383 50
Upper Sandusky 68348 62
Carey 51497 59
 

Topic: applied statistics

Order Description
Address the following prompts about random samples:

First, (1-a) give a concrete example of a research question in which you obtained a truly random sample. (1-b) Explain why, in this case, your sample could be considered “truly random.”

Second, (2-a) give a concrete example of a research question in which you did NOT obtain a truly random sample, yet your conclusion based on that sample would be meaningful and not misleading. (2-b) Explain why, in this case, your conclusion would be meaningful.

Finally, (3-a) give a concrete example of a research question in which you did NOT obtain a truly random sample, and this would cause your conclusion based on these results to be misleading or meaningless. (3-b) Explain why, in this case, your conclusion would not be meaningful.

Evaluation:

You may address the questions within one continuous response or separately, but together the responses should be roughly 1 page, double-spaced. More important than the length is (1) whether you answered the all the questions directly and (2) whether you correctly use and interpret the ideas of (in this case) random sample, representative sample, and biased sample (implicitly or explicitly) in your responses.

In general, try to be as concrete, specific, and explicit as possible, and don’t answer generically or by appealing only to definitions. Also, try to be concise and to directly address the questions. You do not need to include references, and you may use hypothetical examples.