Question

In: Statistics and Probability

The weights (in pounds) of 6 vehicles and the variability of their braking distances (in feet)...

The weights (in pounds) of 6 vehicles and the variability of their braking distances (in feet) when stopping on a dry surface are shown in the table. Can you conclude that there is a significant linear correlation between vehicle weight and variability in braking distance on a dry surface? Use alpha = 0.01

Weight, x 5940 5390 6500 5100 5820 4800

Variability in braking distance, 1.74 1.92 1.93 1.61 1.69 1.50

y

Setup the hypothesis for the test

H0: p ___ 0

Ha: P___ 0

Identify the critical value(s). Round to three decimal places as needed.

Calculate the test statistic.

Solutions

Expert Solution

Weight X Breaking Distance Y   X * Y
5940 1.74 10335.6 35283600 3.0276
5390 1.92 10348.8 29052100 3.6864
6500 1.93 12545 42250000 3.7249
5100 1.61 8211 26010000 2.5921
5820 1.69 9835.8 33872400 2.8561
4800 1.5 7200 23040000 2.25
Total 33550 10.39 58476.2 1.9E+08 18.1371

To Test :-

H0 :-  

H1 :-  

Test Statistic :-


t = 2.075


Test Criteria :-
Reject null hypothesis if

Critical value

-4.6041 < 2.075 < 4.6041
Result :- We fail to Reject null hypothesis


Decision based on P value
P - value = P ( t > 2.075 ) = 0.1066
Reject null hypothesis if P value < level of significance
P - value = 0.1066 > 0.01 ,hence we fail to reject null hypothesis
Conclusion :- We Accept H0

There is no linear correlation between variables.



Related Solutions

The weights (in pounds) of 6 vehicles and the variability of their braking distances (in feet)...
The weights (in pounds) of 6 vehicles and the variability of their braking distances (in feet) when stopping on a dry surface are shown in the table. Can you conclude that there is a significant linear correlation between vehicle weight and variability in braking distance on a dry suffice? Use alph = 0.01. ​Weight, x 5910 5350 6500 5100 5850 4800 Variability in braking​ distance, y 1.79 1.99 1.91 1.55 1.68 1.50 Setup the hypotheis for the test Idenfity the...
The weights​ (in pounds) of 6 vehicles and the variability of their braking distances​ (in feet)...
The weights​ (in pounds) of 6 vehicles and the variability of their braking distances​ (in feet) when stopping on a dry surface are shown in the table. Can you conclude that there is a significant linear correlation between vehicle weight and variability in braking distance on a dry​ surface? use alpha=0.05 weight,X 5960, 5330, 6500, 5100, 5890, 4800 variability in 1.79, 1.95, 1.89, 1.55, 1.65, 1.50 breaking distance,Y set up the hypothesis for the test H o: P=0 H a:...
The weights​ (in pounds) of 6 vehicles and the variability of their braking distances​ (in feet)...
The weights​ (in pounds) of 6 vehicles and the variability of their braking distances​ (in feet) when stopping on a dry surface are shown in the table. Can you conclude that there is a significant linear correlation between vehicle weight and variability in braking distance on a dry​ surface? Use alphaequals0.01. ​Weight, x 5930 5350 6500 5100 5870 4800 Variability in braking​ distance, y 1.71 1.95 1.93 1.65 1.68 1.50
The weights​ (in pounds) of six vehicles and the variability of their braking distances​ (in feet)...
The weights​ (in pounds) of six vehicles and the variability of their braking distances​ (in feet) when stopping on a dry surface are shown in the table. Can you conclude that there is a significant linear correlation between vehicle weight and variability in braking distance on a dry​ surface? Use alphaαequals=0.01 Weight, x   Variability in braking distance, y 5990   1.74 5320   1.99 6500   1.88 5100   1.63 5810   1.62 4800   1.5 set up the hypothesis for the test. identify the critical...
The weights​ (in pounds) of 6 vehicles and the variability of their braking distances​ (in feet) when stopping on a dry surface are shown in the table.
The weights​ (in pounds) of 6 vehicles and the variability of their braking distances​ (in feet) when stopping on a dry surface are shown in the table. Can you conclude that there is a significant linear correlation between vehicle weight and variability in braking distance on a dry​ surface? Use significane of alphaαequals=0.01 Weight, x Variability in braking distance, y 5910 1.74 5330 1.93 6500 1.93 5100 1.64 5870 1.67 4800 1.5 How would you get critical values AND the...
Calvin is 6 feet tall and weighs 225 pounds and is a sophomore at your university....
Calvin is 6 feet tall and weighs 225 pounds and is a sophomore at your university. His mother and father have been overweight as long as he can remember. Calvin works part-time at the local mall and frequently eats whatever he wants while he is there. He purchases snacks from the cookie store, eats lunches in the food court where several options for fast-food exists, and drinks soda pop throughout the day. He is a major and spends much of...
The weights (in pounds) of 30 participants are recorded before and after a 6 week exercise...
The weights (in pounds) of 30 participants are recorded before and after a 6 week exercise program. Before and After Weights Before After 210 207 174 176 150 148 124 130 222 220 287 280 175 168 173 170 264 255 247 250 Before and After Weights Before After 185 184 134 135 157 155 245 242 255 247 148 150 170 165 215 210 309 300 234 230 Before and After Weights Before After 245 240 287 276 200...
A safety engineer records the braking distances of two types of tires. Each randomly selected sample...
A safety engineer records the braking distances of two types of tires. Each randomly selected sample has 35 tires. The results of the tests are shown in the table. At alpha equals 0.10​, can the engineer support the claim that the mean braking distance is different for the two types of​ tires? Assume the samples are randomly selected and that the samples are independent. Complete parts​ (a) through​ (e). Type A 1x1 equals= 43feet 1σ1 equals= 4.7 feet Type B...
Baby weights: Following are weights in pounds for random samples of 19 newborn baby boys and...
Baby weights: Following are weights in pounds for random samples of 19 newborn baby boys and baby girls born in Denver in 2011 . Boxplots indicate that the samples come from populations that are approximately normal. Let μ1 denote the mean weight of boys and μ2 denote the mean weight of girls. Can you conclude that the mean weights differ between boys and girls? Use the =α0.10 level and the P -value method with the table. Boys 7.6 6.4 8.1...
Following are the published weights (in pounds) of all of the team members
115. Following are the published weights (in pounds) of all of the team members of the Sa Francisco 49ers from a previous year 177: 205: 210: 210: 232: 205: 185: 185 178 210: 206 212: 184 174: 185: 242: 188; 212: 215 247:241: 223: 220: 260: 245 259 278: 270 280: 295: 275: 285: 290: 272: 273: 280: 285: 286 200: 215: 185: 230: 250: 241: 190: 260: 250: 302: 265: 290: 276: 228: 265 a. Organize the data from smallest to...
ADVERTISEMENT
ADVERTISEMENT
ADVERTISEMENT