It is advertised that the average braking distance for a small car traveling at 75 miles per hour equals 120 feet. A transportation researcher wants to determine if the statement made in the advertisement is false. She randomly test drives 38 small cars at 75 miles per hour and records the braking distance. The sample average braking distance is computed as 112 feet. Assume that the population standard deviation is 20 feet. (You may find it useful to reference the appropriate table: z table or t table)

a. State the null and the alternative hypotheses for the test.
  

• H₀: μ = 120; H_A: μ ≠ 120

• H₀: μ ≥ 120; H_A: μ < 120

• H₀: μ ≤ 120; H_A: μ > 120

b. Calculate the value of the test statistic and the p-value. (Negative value should be indicated by a minus sign. Round intermediate calculations to at least 4 decimal places and final answer to 2 decimal places.)
  

Find the p-value.
  

• 0.025 p-value < 0.05
• 0.05 p-value < 0.10
• p-value 0.10

• p-value < 0.01

• 0.01 p-value < 0.025

c. Use α = 0.10 to determine if the average breaking distance differs from 120 feet.
  

It is advertised that the average braking distance for a small car traveling at 65 miles per hour equals 120 feet. A transportation researcher wants to determine if the statement made in the advertisement is false. She randomly test drives 34 small cars at 65 miles per hour and records the braking distance. The sample average braking distance is computed as 116 feet. Assume that the population standard deviation is 22 feet. (You may find it useful to reference the appropriate table: z table or t table) b. Calculate the value of the test statistic and the p-value. (Negative value should be indicated by a minus sign. Round intermediate calculations to at least 4 decimal places and final answer to 2 decimal places.)

The data in the table represent the weights of various domestic cars and their miles per gallon in the city for the 2008 model year. For the data from the first 11​ cars, the​ least-squares regression line is y=−0.0062x+42.4755. A twelfth car weighs 2,705 pounds and gets 14 miles per gallon. Compute the coefficient of determination of the expanded data set​ (including the twelfth​ car). What effect does the addition of the twelfth car to the data set have on Rsquared2​?

Car   Weight_(pounds)_x   Miles_per_Gallon_y
1   3765   21
2   3980   19
3   3532   22
4   3174   21
5   2582   27
6   3729   18
7   2601   26
8   3775   18
9   3313   19
10   2991   26
11   2753   26
12   2705   14

1) The coefficient of determination of the expanded data set is

2)How does the addition of the twelfth car to the data set affect Rsquared2​? Select the correct choice below​ and, if​ necessary, fill in the answer box to complete your choice.

a) It increases by __

b) It decreases by __

c) it does not affect it

It is advertised that the average braking distance for a small car traveling at 65 miles per hour equals 120 feet. A transportation researcher wants to determine if the statement made in the advertisement is false. She randomly test drives 37 small cars at 65 miles per hour and records the braking distance. The sample average braking distance is computed as 111 feet. Assume that the population standard deviation is 21 feet. (You may find it useful to reference the appropriate table: z table or t table) a. State the null and the alternative hypotheses for the test. H0: μ = 120; HA: μ ≠ 120 H0: μ ≥ 120; HA: μ < 120 H0: μ ≤ 120; HA: μ > 120 b-1. Calculate the value of the test statistic. (Negative value should be indicated by a minus sign. Round intermediate calculations to at least 4 decimal places and final answer to 2 decimal places.) b-2. Find the p-value. 0.01 p-value < 0.025 0.025 p-value < 0.05 0.05 p-value < 0.10 p-value 0.10 p-value < 0.01 c. Use α = 0.01 to determine if the average breaking distance differs from 120 feet.

To get to a concert in time, a harpsichordist has to drive 122 miles in 1.93 hours. (a) If he drove at an average speed of 52.0 mi/h in a due west direction for the first 1.22 h, what must be his average speed if he is heading 30.0° south of west for the remaining 42.6 min?(b) What is his average velocity for the entire trip?(give magnitude and direction)

If a bridge is above a river approximately 10 miles from the sea with a bridge deck of 170m

What type of concrete is should be used? will it be sulphate resistant concrete or high performance concrete or any other?

What will the Eurocode exposure class be ? will it be XS1 or XD1? or something else?

Will it be EN206/BS8500 type of concrete?

Suppose the Gulfstream G550 is cruising at an altitude and of 41,000 feet. and 559 miles per hour, respectively. If the plane currently weighs 74,950 pounds, how much thrust is required to maintain these flight conditions? The wingspan is 91.5 feet and the wing platform area is 1,137 square feet. The Oswald efficiency factor is 0.9 and the zero-lift drag coefficient is 0.0165.

Homicide and suicide are both intentional means of ending a life. However, the reason for committing a homicide is different from that for suicide and we might expect homicide and suicide rates to be uncorrelated. On the other hand, both can involve some degree of violence, so perhaps we might expect some level of correlation in the rates. The data from 2008–2011 for 26counties in Ohio are shown in the table. Rates are per 100,000 people.

To access the complete data set, click the link for your preferred software format:

Excel  Minitab  JMP  SPSS TI  R  Mac-TXT   PC-TXT  CSV CrunchIt!

(a) Make a scatterplot that shows how suicide rate can be predicted from homicide rate. There is a weak linear relationship, with correlation ?=0.17.

Each of the scatterplots in the choices has a relationship fitted to the plot. Select the plot that corresponds with the correlation of 0.17.

(b) Find the least‑squares regression line for predicting suicide rate from homicide rate, ?+?×(homicide). (Enter your answers rounded to three decimal places.)

?=

?=

(c) Explain in words what the slope of the regression line tells us.

The slope means that for every additional suicide (per 100,000 people) , there is an average increase of 0.126 homicide (per 100,000 people) in these Ohio counties.

The slope means that for every additional homicide (per 100,000 people), there is an average decrease of 0.126 suicide (per 100,000 people) in these Ohio counties.

The slope means that for every additional homicide (per 100,000 people), there is an average decrease of 11.640 suicides (per 100,000 people) in these Ohio counties.

The slope means that for every additional homicide (per 100,000 people), there is an average increase of 0.126 suicide (per 100,000 people) in these Ohio counties.

The slope means that for every additional homicide (per 100,000 people), there is an average increase of 11.640 suicides (per 100,000 people) in these Ohio counties.

(d) Another Ohio county has a homicide rate of 8.0 per 100,000 people. What is the county’s predicted suicide rate? (Enter your answer rounded to three decimal places.)

Predicted suicide rate:

1. The waiting times​ (in minutes) of a random sample of 21 people at a bank have a sample standard deviation of 3.5 minutes. Construct a confidence interval for the population variance sigma squared and the population standard deviation sigma. Use a 99 % level of confidence. Assume the sample is from a normally distributed population. What is the confidence interval for the population variance sigma squared​?

2.You are given the sample mean and the population standard deviation. Use this information to construct the​ 90% and​ 95% confidence intervals for the population mean. Interpret the results and compare the widths of the confidence intervals. If​ convenient, use technology to construct the confidence intervals. A random sample of 55 home theater systems has a mean price of ​$113.00. Assume the population standard deviation is ​$15.20.

Question 1:- A potential investor collected attendance data over a period of 49 days at the North Mall and South Mall theaters in order to determine the difference between the average daily attendances. The North Mall Theater averaged 720 patrons per day with a variance of 100, while the South Mall Theater averaged 700 patrons per day with a variance of 96. Develop an interval estimate for the difference between the average daily attendances at the two theaters. Use a confidence coefficient of 0.95.

Question 2:-Zip, Inc. manufactures Zip drives on two different manufacturing processes. Because the management of this company is interested in determining if process 1 takes less manufacturing time, they selected independent random samples from each process. The results of the samples are shown below. (20 points)

                                          Process 1          Process 2

Sample size                               27               22

Sample mean (in minutes) 10              14

Sample variance                 16             25

1. State the null and alternative hypotheses.

2. Determine the degrees of freedom for the t-test.

3. Compute the test statistic

4. At 95% confidence, test to determine if there is sufficient evidence to indicate that process 1 takes a significantly shorter time to manufacture the Zip drives.

Question 3:-  

Shown below is a portion of computer output for a regression analysis relating to Y (dependent variable) and X (independent variable). (20 points)

ANOVA     

                  df SS

Regression   1 115.064

Residual 13   82.936

Total    

            Coefficients Standard Error

Intercept 15.532                 1.457

x              -1.106               0.261

a. Perform a t-test using the p-value approach and determine whether x and y are related. Let α = .05.

b. Using the p-value approach, perform an F test, and determine whether x and y are related.

c. Compute the coefficient of determination and fully interpret its meaning. Be specific.