# Ashford University Replication Statistics Paper

PART 1

Run the ANOVA: Two-Factor with Replication statistics for the Data File TourisTopia

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In a managerial report,

• Use descriptive statistics to summarize the data from Triple T’s study. Based on descriptive statistics, what are your preliminary conclusions about whether the time spent by visitors to the Triple T website differs by background color or font? What are yourpreliminary conclusions about whether time spent by visitors to the Triple T website differs by different combinations of background color and font?
• Explain whether Triple T has used an observational study or a controlled experiment.
• Use the data from Triple T’s study to test the hypothesis that the time spent by visitors to the Triple T website is equal for the three background colors. Include both factors and their interaction in the ANOVA model, and use a=.05.
• Use the data from Triple T’s study to test the hypothesis that the time spent by visitors to the Triple T website is equal for the three fonts. Include both factors and their interaction in the ANOVA model, and use a=.05.
• Use the data from Triple T’s study to test the hypothesis that time spent by visitors to the Triple T website is equal for the nine combinations of background color and font. Include both factors and their interaction in the ANOVA model, and use a=.05.
• Discuss whether the results of your analysis of the data provide evidence that the time spent by visitors to the Triple T website differs by background color, font, or combination of background color and font. What is your recommendation?
• What recommendations does your ANOVA results support? Use findings from your managerial report to support your recommendations. Be sure to include why you support certain decisions over others. What surprising findings did you come up with during your analysis?
• PART 2
• Run a Regression for the Data File NASCAR
• In a managerial report,Suppose you wanted to predict Winnings (\$) using only the number of poles won (Poles), the number of wins (Wins), the number of top five finishes (Top 5), or the number of top ten finishes (Top 10). Which of these four variables provides the best single predictor of winnings?Develop an estimated regression equation that can be used to predict Winnings (\$) given the number of poles won (Poles), the number of wins (Wins), the number of top five finishes (Top 5), and the number of top ten (Top 10) finishes. Test for individual significance, and then discuss your findings and conclusions.What did you find in your analysis of the data? Were there any surprising results? What recommendations would you make based on your findings? Include details from your managerial report to support your recommendations. Background
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Ariel
301
288
234
381
295
351
298
290
311
355
275
271
210
324
327
200
257
266
205
194
209
292
261
247
259
284
161
291
205
323
Calibri
225
250
173
267
356
253
230
261
294
216
258
216
203
223
159
178
241
312
310
310
251
273
269
121
344
224
181
252
181
253
Tahoma
217
259
234
270
245
239
268
245
273
265
261
193
280
282
227
217
180
285
254
313
201
247
188
198
221
204
208
256
174
167
Driver
Points
Poles
Tony Stewart
2403
Carl Edwards
2403
Kevin Harvick
2345
Matt Kenseth
2330
2319
Jimmie Johnson
2304
Dale Earnhardt Jr.
2290
Jeff Gordon
2287
Denny Hamlin
2284
Ryan Newman
2284
Kurt Busch
2262
Kyle Busch
2246
Clint Bowyer
1047
Kasey Kahne
1041
A.J. Allmendinger
1013
Greg Biffle
997
Paul Menard
947
Martin Truex Jr.
937
Marcos Ambrose
936
Jeff Burton
935
Juan Montoya
932
Mark Martin
930
David Ragan
906
Joey Logano
902
Brian Vickers
846
Regan Smith
820
Jamie McMurray
795
David Reutimann
757
Bobby Labonte
670
David Gilliland
572
Casey Mears
541
Dave Blaney
508
Andy Lally*
398
Robby Gordon
268
J.J. Yeley
192
Wins
1
3
0
3
1
0
1
1
0
3
3
1
0
2
0
3
0
1
0
0
2
2
2
2
0
0
1
1
0
0
0
0
0
0
0
Top 5
5
1
4
3
3
2
0
3
1
1
2
4
1
1
0
0
1
0
1
0
0
0
1
0
0
1
0
0
0
0
0
0
0
0
0
Top 10
9
19
9
12
10
14
4
13
5
9
8
14
4
8
1
3
4
3
5
2
2
2
4
4
3
2
2
1
1
1
0
1
0
0
0
Winnings (\$)
19
6,529,870
26
8,485,990
19
6,197,140
20
6,183,580
14
5,087,740
21
6,296,360
12
4,163,690
18
5,912,830
14
5,401,190
17
5,303,020
16
5,936,470
18
6,161,020
16
5,633,950
15
4,775,160
10
4,825,560
10
4,318,050
8
3,853,690
12
3,955,560
12
4,750,390
5
3,807,780
8
5,020,780
10
3,830,910
8
4,203,660
6
3,856,010
7
4,301,880
5
4,579,860
4
4,794,770
3
4,374,770
2
4,505,650
2
3,878,390
0
2,838,320
1
3,229,210
0
2,868,220
0
2,271,890
0
2,559,500

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