The Toyota Camry is one of the best-selling cars in North America. The cost of a previously owned Camry depends on many factors, including the model year, mileage, and condition. To investigate the relationship between the car’s mileage and the sales price for Camrys, the following data show the mileage and sale price for 19 sales (PriceHub web site, February 24, 2012).
Miles (1,000s) | Price ($1,000s) | ||||
22 | 16.2 | ||||
29 | 16.0 | ||||
36 | 13.8 | ||||
47 | 11.5 | ||||
63 | 12.5 | ||||
77 | 12.9 | ||||
73 | 11.2 | ||||
87 | 13.0 | ||||
92 | 11.8 | ||||
101 | 10.8 | ||||
110 | 8.3 | ||||
28 | 12.5 | ||||
59 | 11.1 | ||||
68 | 15.0 | ||||
68 | 12.2 | ||||
91 | 13.0 | ||||
42 | 15.6 | ||||
65 | 12.7 | ||||
110 | 8.3 |
(d) | How much of the variation in the sample values of price does the model estimated in part (b) explain? |
If required, round your answer to two decimal places. | |
% | |
(e) | For the model estimated in part (b), calculate the predicted price and residual for each automobile in the data. Identify the two automobiles that were the biggest bargains. |
If required, round your answer to the nearest whole number. | |
The best bargain is the Camry # in the data set, which has miles, and sells for $ less than its predicted price. The second best bargain is the Camry # in the data set, which has miles, and sells for $ less than its predicted price. |
|
(f) | Suppose that you are considering purchasing a previously owned Camry that has been driven 30,000 miles. Use the estimated regression equation developed in part (b) to predict the price for this car. |
If required, round your answer to one decimal place. Do not round intermediate calculations. | |
Predicted price: $ | |
Is this the price you would offer the seller? | |
- Select answer -Yes or No? | |
Explain. |
In: Math
What are the issues with large significance values?
In: Math
You discover an isolated population of island squirrels and collect 200 of them, finding leucism 12. Perform a hypothesis test for a difference in the proportions of leucism among this island population and the previously considered population. Report your conclusion at both the a=.01 and a=.05 level.
In: Math
Dry Goods Sales The data is for weekly sales in the dry goods department at a Wal*Mart store in the Northeast. Peak values, I.e. spikes, usually occur at holiday periods. Week 1 is the first week of February 2002. To show continuity, week 1 of 2003 is represented as week 54 since week 53 represents the end of fiscal 2002 and start of the 2003 fiscal year. Dollar values are adjusted in order to disguise true sales figures, but trends in the data are retained for analysis puposes. |
Week | Sales in $ | ||||||||
26 | 15200 | ||||||||
27 | 15600 | ||||||||
28 | 16400 | ||||||||
29 | 15600 | ||||||||
30 | 14200 | ||||||||
31 | 14400 | ||||||||
32 | 16400 | ||||||||
33 | 15200 | ||||||||
34 | 14400 | ||||||||
35 | 13800 | ||||||||
36 | 15000 | ||||||||
37 | 14100 | ||||||||
38 | 14400 | ||||||||
39 | 14000 | ||||||||
40 | 15600 | ||||||||
41 | 15000 | ||||||||
42 | 14400 | ||||||||
43 | 17800 | ||||||||
44 | 15000 | ||||||||
45 | 15200 | ||||||||
46 | 15800 | ||||||||
47 | 18600 | ||||||||
48 | 15400 | ||||||||
49 | 15500 | ||||||||
50 | 16800 | ||||||||
51 | 18700 | ||||||||
52 | 21400 | ||||||||
53 | 20900 | ||||||||
54 | 18800 | ||||||||
55 | 22400 | ||||||||
56 | 19400 | ||||||||
57 | 20000 | ||||||||
58 | 18100 | ||||||||
59 | 18000 | ||||||||
60 | 19600 | ||||||||
61 | 19000 | ||||||||
62 | 19200 | ||||||||
63 | 18000 | ||||||||
64 | 17600 | ||||||||
65 | 17200 | ||||||||
66 | 19800 | ||||||||
67 | 19600 | ||||||||
68 | 19600 | ||||||||
69 | 20000 | ||||||||
70 | 20800 | ||||||||
71 | 22800 | ||||||||
72 | 23000 | ||||||||
73 | 20800 | ||||||||
74 | 25000 | ||||||||
75 | 30600 | ||||||||
76 | 24000 | ||||||||
77 |
21200 |
1.) Can you identify at least 6 holiday periods or special events that cause the spikes in the data?
a.) In each case give the week number, date, and what holiday or special event it represents
b.) Which holiday results in the maximum sales for this department and how much are the sales?
2.) Generate three linear models for this data. Each linear model should be generated from a pair of data points.
a.) For each linear model, find the equation of the line. Show your work. Write the equation in slope intercept form.
b.) For each linear model discuss the meaning of the slope and y-intercept. Also provide an analysis as to why you like or dislike that particular model
c.) Discuss the rationale behind the model that you believe best predicts future results.
3.) Predict and analyze sales for the next four weeks
a.) Using your most preferred linear model, predict sales for the next four weeks and show calculations
b.) Based on your preferred linear model, compute the percent rate of increase (y2-y1)/y1 for the next four weeks
4.) If you were a manager of this department store, what recommendation would you make to the person in charge of inventory?
In: Math
The mean systolic blood pressure for people in the United States is reported to be 122 millimeters of mercury (mmHg) with a standard deviation of 22.8 millimeters of mercury. The wellness department of a large corporation is investigating if the mean systolic blood pressure is different from the national mean. A random sample of 200 employees in a company were selected and found to have an average systolic blood pressure of 124.7 mmHg.
a) What is the probability a random employees blood pressure is higher than 135 mmHg.
b) What is the probability that 200 randomly selected employees mean blood pressure is greater than 127 mmHg.
c) The wellness department is providing a new health program to their employees. Past studies have shown 9.9 % of their employees have high blood pressure. Find the probability that if the wellness department examines 200 randomly selected employees, less than 12 employees will have high systolic blood pressure. Do you think the new program significantly lowers the number of employees with a high blood pressure.
In: Math
Age | HRS1 |
58 | 32 |
24 | 46 |
32 | 40 |
29 | 40 |
34 | 86 |
49 | 40 |
60 | 40 |
78 | 25 |
39 | 5 |
67 | 15 |
22 | 40 |
In: Math
The weight of navel oranges of a domestic farm is normally distributed with a mean of 8.0oz and a standard deviation of 1.5oz. Suppose that you bought 10 oranges randomly sampled.
a) what are the mean of the sampling distribution and the standard error of the mean?
b) what is the probability that the sample mean is between 8.5 and 10.0 oz?
c) The probability is 90% that the sample mean will be between what two values symmetrically distributed around the population mean?
In: Math
By utilising Annexure A, answer the following questions:
Process |
Mean |
Standard Deviation |
Lower Specification |
Upper Specification |
1 |
6.0 |
0.14 |
5.5 |
6.7 |
2 |
7.5 |
0.10 |
7.0 |
8.0 |
3 |
4.6 |
0.12 |
4.3 |
4.9 |
Numbers of observations in subgroup n |
Factor for X- bar Chart A2 |
Factors for R Charts Lower control limit D3 |
Factors for R Charts Upper control limit D4 |
2 |
1.88 |
0 |
3.27 |
3 |
1.02 |
0 |
2.57 |
4 |
0.73 |
0 |
2.28 |
5 |
0.58 |
0 |
2.11 |
6 |
0.48 |
0 |
2.00 |
7 |
0.42 |
0.08 |
1.92 |
8 |
0.37 |
0.14 |
1.86 |
9 |
0.34 |
0.18 |
1.82 |
10 |
0.31 |
0.22 |
1.78 |
11 |
0.29 |
0.26 |
1.74 |
12 |
0.27 |
0.28 |
1.72 |
13 |
0.25 |
0.31 |
1.69 |
14 |
0.24 |
0.33 |
1.67 |
15 |
0.22 |
0.35 |
1.65 |
16 |
0.21 |
0.36 |
1.64 |
17 |
0.20 |
0.38 |
1.62 |
18 |
0.19 |
0.39 |
1.61 |
19 |
0.19 |
0.40 |
1.60 |
20 |
0.18 |
0.41 |
1.59 |
In: Math
Carson Trucking is considering whether to expand its regional service center in Mohab, UT. The expansion requires the expenditure of $10,500,000 on new service equipment and would generate annual net cash inflows from reduced costs of operations equal to $4,000,000 per year for each of the next 7 years. In year 7 the firm will also get back a cash flow equal to the salvage value of the equipment, which is valued at $1.1 million. Thus, in year 7 the investment cash inflow totals $5,100,000. Calculate the project's NPV using a discount rate of 7 percent.
If the discount rate is 7 percent, then the project's NPV is $ ___
In: Math
We want to test the claim that people are taller in the morning than in the evening. Morning height and evening height were measured for 30 randomly selected adults and the difference (morning height) − (evening height) for each adult was recorded in the table below. Use this data to test the claim that on average people are taller in the morning than in the evening. Test this claim at the 0.01 significance level.
(a) In mathematical notation, the claim is which of the following? μ = 0 μ ≠ 0 μ > 0 μ < 0 (b) What is the test statistic? Round your answer to 2 decimal places. t x =(c) Use software to get the P-value of the test statistic. Round to 4 decimal places. P-value = (d) What is the conclusion regarding the null hypothesis? reject H0fail to reject H0 (e) Choose the appropriate concluding statement. The data supports the claim that on average people are taller in the morning than in the evening. There is not enough data to support the claim that on average people are taller in the morning than in the evening. We reject the claim that on average people are taller in the morning than in the evening. We have proven that on average people are taller in the morning than in the evening. |
DATA ( n = 30 )
AM-PM Height
Difference
cm |
-0.13 |
0.26 |
0.65 |
0.21 |
-0.40 |
-0.01 |
-0.06 |
0.60 |
-0.15 |
0.60 |
0.78 |
0.32 |
1.18 |
0.15 |
0.27 |
-0.26 |
-0.06 |
0.95 |
-0.26 |
0.07 |
0.59 |
-0.09 |
-0.01 |
-0.24 |
0.25 |
0.19 |
0.74 |
0.43 |
0.20 |
-0.11 |
In: Math
The following data come from the 2016 ANES, V36 and V87W, both recoded into 3 categories. One question asked about party identification. The other asked about support for building a wall on the border between the United States and Mexico. The results were as follows:
Partisanship |
Oppose |
Not sure |
Favor |
Democrat |
620 |
217 |
199 |
Independent |
401 |
327 |
602 |
Republican |
155 |
218 |
874 |
Total |
1176 |
762 |
1675 |
Calculate appropriate percentages for the table, justify your choice of row, column, or total percentages, and comment on the relationship.
In: Math
A factorial experiment was designed to test for any significant differences in the time needed to perform English to foreign language translations with two computerized language translators. Because the type of language translated was also considered a significant factor, translations were made with both systems for three different languages: Spanish, French, and German. Use the following data for translation time in hours.
Language | |||
Spanish | French | German | |
System 1 | 7 | 14 | 14 |
11 | 18 | 18 | |
System 2 | 9 | 14 | 19 |
13 | 16 | 25 |
Test for any significant differences due to language translator system (Factor A), type of language (Factor B), and interaction. Use = .05.
Source of Variation | Sum of Squares | Degrees of Freedom | Mean Square | F | p-value |
Factor A | |||||
Factor B | |||||
Interaction | |||||
Error | |||||
Total |
In: Math
A high school teacher hypothesizes a negative relationship
between performance in exams and performance in presentations. To
examine this, the teacher computes a correlation of 0.58 from a
random sample of 18 students from class. What can the teacher
conclude with an α of 0.01?
a) Compute the appropriate test statistic(s) to
make a decision about H0.
(Hint: Make sure to write down the null and alternative hypotheses
to help solve the problem.)
critical value = ; test statistic =
Decision: ---Select--- Reject H0 Fail to reject H0
b) Compute the corresponding effect size(s) and
indicate magnitude(s).
If not appropriate, input and/or select "na" below.
effect size = ; ---Select--- na trivial
effect small effect medium effect large effect
c) Make an interpretation based on the
results.
There is a significant positive relationship between performance in exams and performance in presentations.There is a significant negative relationship between performance in exams and performance in presentations. There is no significant relationship between performance in exams and performance in presentations.
In: Math
a human resource survey revealed that 30% of job applicants cheat on their psychometric test. use the binomial formula to find the probability that the number of job applicants in a sample of 14 who cheat on their psychometric test is:
a. exactly 8
b. less than 2
c. at least 1
In: Math
A clinical trial is conducted comparing a new pain reliever for arthritis to a placebo. Participants are randomly assigned to receive the new treatment or a placebo and the outcome is pain relief within 30 minutes. The data are shown here.
Pain Relief | No Pain Relief | |
New Medication | 45 | 75 |
Placebo | 20 | 100 |
Is there a significant difference in the proportions of
patients reporting pain relief?
Run the test at a 5% level of significance.
H0: p1= p2(equivalent to RD = 0, RR=1 or OR=1)
Can they reject the H0?
Group of answer choices
Yes, Reject H0, there is a statistically significant difference in the proportions of patients reporting pain relief in the new medication and placebo groups
No, Fail to Reject H0, there is no statistically significant difference in the proportions of patients reporting pain relief between the new medication and placebo groups
Not enough information to answer this research question
In: Math