Level of Significance - Calculated 10. 11 12 13 14 15 16 17 18 19 Ho: v₁-20 20 Ha: v₁->0 Degrees of Freedom (df) t value Margin of Error Point Extimate of Difference Lower Limit Upper Limit Calculated Estimate of Variance Squared/([Car A Sample Size -1) (Car A Sample Standard Deviation Squared/Car A Sample Size)Squared +(1/(Car B Sample Size -1) (Car B Sample Standard Deviation Squared/Car A 0.00 Sample Size)Squared =TINV(probability-use alpha cell,deg freedom-use df cell) t value Standard Error #N/A =E6 2/((1/(C2-1)) (C4 2/C2r2+(1/(D2-1) (D4 2/ #N/A #N/A #N/A #N/A #N/A 22 23 24 21 Comparison of 2 cars gas mileage testing to see if Car A is better than Car B Level of Significance - Given Test Statistic - Calculate p-value calculated 0.050 =((C3-D3)-0)/SQRT((2.56)2/24+(1.81) 2/28) #N/A Use = TDIST(Test Statistic cell location, df cell location, enter the number of tails of 1) #N/A 25 Rule/Decision Statement: 26 27 CV tscore of alpha - calculated Use -T.INV(alph cell location, df cell location) #N/A 28 29 Rule/Decision Statement: 30 31 32 33 34 35 CAR A CAR B 2 Sample Size 24 28 3 Sample Mean (mpg) 29.8 27.3 4 Sample Standard Deviation (n 2.56 1.81 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 Ho: u₁-20 20 Ha: v₁-> 0 Estimate of Variance - Calculated Standard Error - Calculated Confidence Coefficient - Given Level of Significance - Calculated Degrees of Freedom (df) value Margin of Error Point Estimate of Difference Lower Limit Upper Limit 0.9 Car A Sample Standard Deviation Squared/Car A Sample Size plus Car B Sample Standard Deviation Squared/Car B Sample Size The Square Root of the Estimate of Variance Calculated Estimate of Variance Squared/1/Car A Sample Size -1) (Car A Sample Standard Deviation Squared/Car A Sample Size)Squared +(1/(Car B Sample Size-1)*(Car B Sample Standard Deviation Squared/Car A 0.00 Sample Size Squared =TINV probability-use alpha cell deg freedom-use df cell) t value Standard Error #N/A #N/A #N/A =E62/((1/(C2-1)) (C4 2/C2)2+(1/(D2-1)* (D4 2/D212) #N/A #N/A #N/A #N/A #N/A 21 Comparison of 2 cars gas mileage testing to see if Car A is better than Car B 22 23 24 25 Rule/Decision Statement: 26 Level of Significance - Given Test Statistic - Calculate p-value calculated 0.050 =((C3-D3)-0)/SQRT((2.56)2/24+(1.81)^2/28) Use TDIST(Test Statistic cell location, df cell location, enter the number of tails of 1) #N/A #N/A

Level of Significance - Calculated 10. 11 12 13 14 15 16 17 18 19 Ho: v₁-20 20 Ha: v₁->0 Degrees of Freedom (df) t value Margin of Error Point Extimate of Difference Lower Limit Upper Limit Calculated Estimate of Variance Squared/([Car A Sample Size -1) (Car A Sample Standard Deviation Squared/Car A Sample Size)Squared +(1/(Car B Sample Size -1) (Car B Sample Standard Deviation Squared/Car A 0.00 Sample Size)Squared =TINV(probability-use alpha cell,deg freedom-use df cell) t value Standard Error #N/A =E6 2/((1/(C2-1)) (C4 2/C2r2+(1/(D2-1) (D4 2/ #N/A #N/A #N/A #N/A #N/A 22 23 24 21 Comparison of 2 cars gas mileage testing to see if Car A is better than Car B Level of Significance - Given Test Statistic - Calculate p-value calculated 0.050 =((C3-D3)-0)/SQRT((2.56)2/24+(1.81) 2/28) #N/A Use = TDIST(Test Statistic cell location, df cell location, enter the number of tails of 1) #N/A 25 Rule/Decision Statement: 26 27 CV tscore of alpha - calculated Use -T.INV(alph cell location, df cell location) #N/A 28 29 Rule/Decision Statement: 30 31 32 33 34 35 CAR A CAR B 2 Sample Size 24 28 3 Sample Mean (mpg) 29.8 27.3 4 Sample Standard Deviation (n 2.56 1.81 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 Ho: u₁-20 20 Ha: v₁-> 0 Estimate of Variance - Calculated Standard Error - Calculated Confidence Coefficient - Given Level of Significance - Calculated Degrees of Freedom (df) value Margin of Error Point Estimate of Difference Lower Limit Upper Limit 0.9 Car A Sample Standard Deviation Squared/Car A Sample Size plus Car B Sample Standard Deviation Squared/Car B Sample Size The Square Root of the Estimate of Variance Calculated Estimate of Variance Squared/1/Car A Sample Size -1) (Car A Sample Standard Deviation Squared/Car A Sample Size)Squared +(1/(Car B Sample Size-1)(Car B Sample Standard Deviation Squared/Car A 0.00 Sample Size Squared =TINV probability-use alpha cell deg freedom-use df cell) t value Standard Error #N/A #N/A #N/A =E62/((1/(C2-1)) (C4 2/C2)2+(1/(D2-1) (D4 2/D212) #N/A #N/A #N/A #N/A #N/A 21 Comparison of 2 cars gas mileage testing to see if Car A is better than Car B 22 23 24 25 Rule/Decision Statement: 26 Level of Significance - Given Test Statistic - Calculate p-value calculated 0.050 =((C3-D3)-0)/SQRT((2.56)2/24+(1.81)^2/28) Use TDIST(Test Statistic cell location, df cell location, enter the number of tails of 1) #N/A #N/A

Calculus For The Life Sciences

2nd Edition

ISBN:9780321964038

Author:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.

Publisher:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.

Chapter13: Probability And Calculus

Section13.3: Special Probability Density Functions

Problem 16E

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Related questions

Question

Please answer the question in excel and show the exact formulas used. The sample size , sample mean, and sample standard deviation is in the picture at the top in the table. Please show it in excel and give excel formulas.

Level of Significance - Calculated
10.
11
12
13
14
15
16
17
18
19 Ho: v₁-20
20 Ha: v₁->0
Degrees of Freedom (df)
t value
Margin of Error
Point Extimate of Difference
Lower Limit
Upper Limit
Calculated
Estimate of Variance Squared/([Car A Sample Size -1) (Car A Sample
Standard Deviation Squared/Car A Sample Size)Squared +(1/(Car B
Sample Size -1) (Car B Sample Standard Deviation Squared/Car A
0.00 Sample Size)Squared
=TINV(probability-use alpha cell,deg freedom-use df cell)
t value Standard Error
#N/A
=E6 2/((1/(C2-1)) (C4 2/C2r2+(1/(D2-1) (D4 2/
#N/A
#N/A
#N/A
#N/A
#N/A
22
23
24
21 Comparison of 2 cars gas mileage testing to see if Car A is better than Car B
Level of Significance - Given
Test Statistic - Calculate
p-value calculated
0.050
=((C3-D3)-0)/SQRT((2.56)2/24+(1.81) 2/28)
#N/A
Use = TDIST(Test Statistic cell location, df cell location, enter the number
of tails of 1)
#N/A
25
Rule/Decision Statement:
26
27
CV tscore of alpha - calculated
Use -T.INV(alph cell location, df cell location)
#N/A
28
29
Rule/Decision Statement:
30
31
32
33
34
35

CAR A
CAR B
2 Sample Size
24
28
3 Sample Mean (mpg)
29.8
27.3
4 Sample Standard Deviation (n
2.56
1.81
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19 Ho: u₁-20
20 Ha: v₁-> 0
Estimate of Variance - Calculated
Standard Error - Calculated
Confidence Coefficient - Given
Level of Significance - Calculated
Degrees of Freedom (df)
value
Margin of Error
Point Estimate of Difference
Lower Limit
Upper Limit
0.9
Car A Sample Standard Deviation Squared/Car A Sample Size plus Car B
Sample Standard Deviation Squared/Car B Sample Size
The Square Root of the Estimate of Variance
Calculated
Estimate of Variance Squared/1/Car A Sample Size -1) (Car A Sample
Standard Deviation Squared/Car A Sample Size)Squared +(1/(Car B
Sample Size-1)*(Car B Sample Standard Deviation Squared/Car A
0.00 Sample Size Squared
=TINV probability-use alpha cell deg freedom-use df cell)
t value Standard Error
#N/A
#N/A
#N/A
=E62/((1/(C2-1)) (C4 2/C2)2+(1/(D2-1)* (D4 2/D212)
#N/A
#N/A
#N/A
#N/A
#N/A
21 Comparison of 2 cars gas mileage testing to see if Car A is better than Car B
22
23
24
25
Rule/Decision Statement:
26
Level of Significance - Given
Test Statistic - Calculate
p-value calculated
0.050
=((C3-D3)-0)/SQRT((2.56)2/24+(1.81)^2/28)
Use TDIST(Test Statistic cell location, df cell location, enter the number
of tails of 1)
#N/A
#N/A

Definition Definition Measure of central tendency that is the average of a given data set. The mean value is evaluated as the quotient of the sum of all observations by the sample size. The mean, in contrast to a median, is affected by extreme values. Very large or very small values can distract the mean from the center of the data. Arithmetic mean: The most common type of mean is the arithmetic mean. It is evaluated using the formula: μ = 1 N ∑ i = 1 N x i Other types of means are the geometric mean, logarithmic mean, and harmonic mean. Geometric mean: The nth root of the product of n observations from a data set is defined as the geometric mean of the set: G = x 1 x 2 ... x n n Logarithmic mean: The difference of the natural logarithms of the two numbers, divided by the difference between the numbers is the logarithmic mean of the two numbers. The logarithmic mean is used particularly in heat transfer and mass transfer. ln x 2 − ln x 1 x 2 − x 1 Harmonic mean: The inverse of the arithmetic mean of the inverses of all the numbers in a data set is the harmonic mean of the data. 1 1 x 1 + 1 x 2 + ...

Expert Solution