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 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
Solutions
Expert Solution
From the given data, the following Table is calculated:
| X | Y | XY | X2 | Y2 |
| 5930 | 1.71 | 10140.3 | 35164900 | 2.9241 |
| 5350 | 1.95 | 10432.5 | 28622500 | 3.8025 |
| 6500 | 1.93 | 12545 | 42250000 | 3.7249 |
| 5100 | 1.65 | 8415 | 26010000 | 2.7225 |
| 5870 | 1.68 | 9861.6 | 34456900 | 2.8224 |
| 4800 | 1.50 | 7200 | 23040000 | 2.25 |
| Total = 33550 | 10.42 | 58594.4 | 189544300 | 18.2464 |
H0: Null Hypothesis: 
= 0
HA: Alternative Hypothesis: 
0
Test statistic is given by:
= 0.01
ndf = n - 2 = 6 - 2 = 4
From Table, critical values of t = 
4.6041
Since the calculated value of t = 1.5356 is lessthan critical value of t = 4.6041, the difference is not significant. Fail to reject null hypothesis.
Conclusion:
We cannot conclude that there is a significant linear correlation between vehicle weight and variability in braking distance on a dry surface
orchestra answered 1 year agoRelated 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 =
0.01
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...
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 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
Latest Questions
- “Triangle Guessing” game in Python The program accepts the lengths of three (3) sides of a...
- THIS PROGRAM HAS TO BE WRITTEN IN C Single function to perform the parity computation on...
- Consider a buffer system consisting of Benzoic acid (pKa = 4.20) and sodium benzoate, a) Would...
- Decision Variables S T Minimize 1.8S + 2.20T Subject to: Potassium 5S + 8T >= 200...
- A neurologist needs to counsel a stroke victim and her husband about possible outcomes, treatment options,...
- Case Study: Personal Beliefs in the Workplace Don Shakow was a prominent professional who worked in...
- 1: Competency framework usage is the modern best practice in management. What is meant by competency...
ADVERTISEMENT