Testing at the .01 level of significance if the size of the home is a useful predictor of the selling prices of homes (after accounting for the effect of bedrooms), what is the value of the test statistic?

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“A realtor used the regression model Y =β 0 + β 1X1 + β 2X2 + e to predict selling prices of homes (in the thousands of $). The variable X1 represents home size (square feet) and X2 represents number of bedrooms. The following information is available:

Predictor

Constant: coefficient 26.28 Standard Error 22.88
Size: coefficient 0.12352 Standard Error 0.02435
Bedrooms: coefficient 20.183 Standard Error 6.697

ANOVA
Source DF SS F

Regression: F 293.29
Residual: SS 219.6
Total: DF 10

a. Testing at the .01 level of significance if the size of the home is a useful predictor of the selling prices of homes (after accounting for the effect of bedrooms), what is the value of the test statistic?

Test to see if a house with more bedrooms sells for more.

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“A realtor used the regression model Y =β 0 + β 1X1 + β 2X2 + e to predict selling prices of homes (in the thousands of $). The variable X1 represents home size (square feet) and X2 represents number of bedrooms. The following information is available:

Predictor

Constant: coefficient 26.28 Standard Error 22.88
Size: coefficient 0.12352 Standard Error 0.02435
Bedrooms: coefficient 20.183 Standard Error 6.697

ANOVA
Source DF SS F

Regression: F 293.29
Residual: SS 219.6
Total: DF 10

b. Test to see if a house with more bedrooms sells for more.
(i) State Ho and Ha
(ii) Calculate the value of the test statistic
(iii) What is your conclusion? Use 5% level of significance.

Using the regression results from above what is the predicted selling price of a home with 6 bedrooms and 3200 feet? Is the overall model significant?

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“A realtor used the regression model Y =β 0 + β 1X1 + β 2X2 + e to predict selling prices of homes (in the thousands of $). The variable X1 represents home size (square feet) and X2 represents number of bedrooms. The following information is available:

Predictor

Constant: coefficient 26.28 Standard Error 22.88
Size: coefficient 0.12352 Standard Error 0.02435
Bedrooms: coefficient 20.183 Standard Error 6.697

ANOVA
Source DF SS F

Regression: F 293.29
Residual: SS 219.6
Total: DF 10

c. Using the regression results from above what is the predicted selling price of a home with 6 bedrooms and 3200 feet? Is the overall model significant?

How many participants need to be enrolled in each group to have 90% chance of detecting a significant difference using a two-sided test with a a= .05 if compliance is perfect?

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Suppose we assume that the incidence of MI is .005 per year among participants who actually take placebo and that aspirin prevents 20% of MI (i.e. relative risk = p1/p2 = 0.8). We also assume that the duration of the study is 5 years and that the dropout rate in the aspirin group = 10% and the drop-in rate of the placebo group = 5 %.

How many participants need to be enrolled in each group to have 90% chance of detecting a significant difference using a two-sided test with a a= .05 if compliance is perfect?

If the test contains 250 questions, what is the probability that Jodi will score between 70% and 80%? You see that Jodi’s score on the longer test is more likely to be close to her “true score.”

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Multiple-choice tests. Here is a simple probability model for multiple-choice tests. Suppose that each student has probability p of correctly answering a question chosen at random from a universe of possible questions. (A strong student has a higher p than a weak student.) Answers to different questions are independent.

(a) Jodi is a good student for whom p = 0.75. Use the Normal approximation to find the probability that Jodi scores between 70% and 80% on a 100-question test.

(b) If the test contains 250 questions, what is the probability that Jodi will score between 70% and 80%? You see that Jodi’s score on the longer test is more likely to be close to her “true score.”

Find the likelihood of selecting a sample with a mean of more than $121,000 but less than $135,000. (Round z value to 2 decimal places and final answer to 4 decimal places.

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Information from the American Institute of Insurance indicates the mean amount of life insurance per household in the United States is $130,000. This distribution follows the normal distribution with a standard deviation of $39,000.

(a)

If we select a random sample of 68 households, what is the standard error of the mean? (Round your answer to the nearest whole number.)

Standard error of the mean

(b) What is the expected shape of the distribution of the sample mean?

Sample mean: Click to select:
-Uniform
-Unknown
-Not normal, the standard deviation is unknown
-Normal

(c)

What is the likelihood of selecting a sample with a mean of at least $135,000? (Round z value to 2 decimal places and final answer to 4 decimal places.)

Probability

(d)

What is the likelihood of selecting a sample with a mean of more than $121,000? (Round z value to 2 decimal places and final answer to 4 decimal places.)

Probability

(e)

Find the likelihood of selecting a sample with a mean of more than $121,000 but less than $135,000. (Round z value to 2 decimal places and final answer to 4 decimal places.

For a random sample of 64 men, what is the likelihood that the age at which they were married for the first time is less than 24.9 years?

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The mean age at which men in the United States marry for the first time follows the normal distribution with a mean of 24.6 years. The standard deviation of the distribution is 2.9 years.

For a random sample of 64 men, what is the likelihood that the age at which they were married for the first time is less than 24.9 years? (Round z value to 2 decimal places. Round your answer to 4 decimal places.)

Crossett Trucking Company claims that the mean weight of its delivery trucks when they are fully loaded is 6,000 pounds and the standard deviation is 150 pounds. Forty trucks are randomly selected and weighed. Within what limits will 95 percent of the sample means occur?

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Crossett Trucking Company claims that the mean weight of its delivery trucks when they are fully loaded is 6,000 pounds and the standard deviation is 150 pounds. Assume that the population follows the normal distribution. Forty trucks are randomly selected and weighed.

Within what limits will 95 percent of the sample means occur? (Round your z-value to 2 decimal places and final answers to 1 decimal place.)

.What is the average number of customers who are at the checkout desk, either waiting or currently being served?

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.Atlantic Video, a small video rental store in Los Angeles, is open 24 hours a day, and experiences customers arriving around the clock. A recent analysis done by the store manager indicates that there are 30 customers arriving every hour, with a standard deviation of inter-arrival times of 2 minutes. This arrival pattern is consistent and is independent of the time of day. The checkout is currently operated by one employee, who needs on average 1.7 minutes to check out a customer. The standard deviation of this check-out time is 3 minutes, primarily as a result of customers taking home different numbers of videos.

a.If you assume that every customer rents at least one video (i.e., has to go to the check-out), what is the average time a customer has to wait in line before getting served by the checkout employee, not including the actual checkout time?
b.If there are no customers requiring checkout, the employee is sorting returned videos, of which there are always plenty waiting to be sorted. How many videos can the employee sort over an 8-hour shift (assume no breaks) if it takes exactly 1.5 minutes to sort a single video?
c.What is the average number of customers who are at the checkout desk, either waiting or currently being served?
d.Now assume for this question only that 10 percent of the customers do not rent a video at all and therefore do not have to go through checkout. What is the average time a customer has to wait in line before getting served by the checkout employee, not including the actual checkout time? Assume that the coefficient of variation for the arrival process remains the same as before.
e.As a special service, the store offers free popcorn and sodas for customers waiting in line at the checkout desk. (Note: The person who is currently being served is too busy with paying to eat or drink.) The store owner estimates that every minute of customer waiting time costs the store 75 cents because of the consumed food. What is the optimal number of employees at checkout? Assume an hourly wage rate of $10 per hour. (Hint: Compare the costs of employing 1,2,3 and 4 workers and then pick the best.)

Prepare a PERT chart and identify the critical path. Prepare a GANTT chart consistent with the PERT chart. What is the total elapsed time for the meal preparation?

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A project requires the following steps sequenced as shown. Prepare a PERT chart and identify the critical path. Prepare a GANTT chart consistent with the PERT chart. What is the total elapsed time for the meal preparation?

Prepare a meal with salad & pizza
Step Description Predecessors #of minutes
1 Prepare Crust 10
2 Place crust on pizza pan 1 5
3 Prepare pizza ingredients 5
4 Add ingredients to pizza 2,3 5
5 Heat oven 25
6 Cook pizza 4,5 15
7 Mix salad dressing 10
8 Prepare salad ingredients 10
9 Assemble Salad 7,8 5
10 Remove pizza from oven and cut to size 6 5
11 Serve meal 9,10 5

a. PERT Chart
b. The critical path is : ______________________________
c. GANTT chart

Step Description Minutes elapsed time
5 10 15 20 25 30 35 40 45 50
1 Prepare Crust
2 Place crust on pizza pan
3 Prepare pizza ingredients
4 Add ingredients to pizza
5 Heat oven
6 Cook pizza
7 Mix salad dressing
8 Prepare salad ingredients
9 Assemble Salad
10 Remove pizza from oven and cut
11 Serve meal

d. What is the total elapsed time for the meal preparation _____ minutes.

Construct a p-chart that plots the percentage of patients unsatisfied with their meals. Set the control limits to include 99.73% of the random variation in meal satisfaction.

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Detroit Central Hospital is trying to improve its image by
providing a positive experience for its patients and their relatives. Part
of the “image” program involves providing tasty, inviting patient meals
that are also healthful. A questionnaire accompanies each meal served,
asking the patient, among other things, whether he or she is satisfied or
unsatisfied with the meal. A 100-patient sample of the survey results
over the past 7 days yielded the following data:
Day No. of Unsatisfied Patients Sample Size
1 24 100
2 22 100
3 8 100
4 15 100
5 10 100
6 26 100
7 17 100
Construct a p-chart that plots the percentage of patients unsatisfied with
their meals. Set the control limits to include 99.73% of the random variation
in meal satisfaction. Comment on your resu

Please list and discuss regression statistics and explain the different variables that are measured by these statistics? Can you provide examples?

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Please list and discuss regression statistics and explain the different variables that are measured by these statistics? Can you provide examples?

Information from the American Institute of Insurance indicates the mean amount of the insurance per household in the United States is $ 110,000. The distribution follows the normal distribution with a standard deviation of $ 40,000.

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Information from the American Institute of Insurance indicates the mean amount of the
insurance per household in the United States is $ 110,000. The distribution follows the normal distribution
with a standard deviation of $ 40,000.

a. If we select a random sample of 50 households, what is the standard error of the men ?

b. What is the expected shape of the distribution of the sample mean ?

c. What is the likelihood of selecting a sample with a mean of at lease $ 112,000 ?

d. What is the likelihood of selection a sample with a mean of more than $100,000 ?

e. Find the likelihood of selecting a sample with a mean of more than $ 100,000 but
less than $ 112.000.

The task will be completed if any one team completes it in the allotted time. Assuming that the teams work independently, what is the probability that the task will not be completed in time.

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Hoping to increase the chances of reaching a performance goal, the director of a research project has assigned three separate research teams the same task. The director estimates that the team reliabilities are 0.9, 0.8, and 0.7 for successfully completing the task in the allotted time. The task will be completed if any one team completes it in the allotted time. Assuming that the teams work independently, what is the probability that the task will not be completed in time.

hese members of soccer discourse community could enjoys soccer outside from fields. Such as watching soccer game, playing video soccer games. Most of the time this community members likes to watch soccer games.

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These members of soccer discourse community could enjoys soccer outside from fields. Such as watching soccer game, playing video soccer games. Most of the time this community members likes to watch soccer games. About soccer, there are many soccer festivals happening across the world. Every specific years, important soccer tournaments are held. For example, for the nation teams, there are events like the “World cup”,”Euro cup”,”Asia cup” and ”America cup” and “Africa cup”. And also there are many tournaments and cups for the club team. So every almost year, members have gathered together and forms group that support their favorite soccer team through in house, pubs, restaurants that these matches make them so excited and crazy. Otherwise, they also play a video game related with soccer. The funny thing is when two players or four players whose playing in team, play against each other, the other members who isn’t playing, forms group and support like real soccer matches.

Please determine which proposal will be the final outcome and explain the decision making process briefly in one paragraph.

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Please solve the following game:

Assume that a total $100 grant will be shared by the three researchers, X, Y, and Z. Each person is rational and selfish. There are six proposals with different shares of (X, Y, Z) for choices as the following.

Proposal I: (X, Y, Z) = (50, 40, 10)
Proposal II: (X, Y, Z) = (60, 10, 30)
Proposal III: (X, Y, Z) = (40, 20, 40)
Proposal IV: (X, Y, Z) = (20, 30, 50)
Proposal V: (X, Y, Z) = (30, 50, 20)
Proposal VI: (X, Y, Z) = (20, 50, 30)

The rule of choosing the final proposal is simple. First, Z is the person to determine who (either X or Y) is the proposal raiser. Then the proposal raiser chooses a particular proposal. Finally, the last person has the right to pass it or reject it. If the last person’s payoff is the smallest among the three, then the proposal will be rejected and no one will get anything. The decision making process can be done by only one time.

Please determine which proposal will be the final outcome and explain the decision making process briefly in one paragraph.

What is the relationship between correlation and causation? Why is it important to understand this relationship?

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What is the relationship between correlation and causation? Why is it important to understand this relationship? Provide the necessary information and resources used to support your summary. Responses to each question should be at least -300 words.

Do you think many organizations use probability/impact matrixes? What about sensitivity analysis or simulation?

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Do you think many organizations use probability/impact matrixes? What about sensitivity analysis or simulation? When does it make sense to use each tool? 200 Words

If Brigg has $3,000, having utility function U(x) = ln(x) – 0.0005x, where x is total wealth which Alternative he should choose A or B?

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Jonna is in market to buy a new laptop. Six different machines are under consideration. All laptops are essentially the same, but they vary in price and reliability. The least expensive model is also the least reliable, the most expensive is the most reliable, and the others are in between. The laptops are described as follows:

A Price $1260 Expected number of days in the shop per year = 5.5
B Price $1750 Expected number of days in the shop per year = 2
C Price $860 Expected number of days in the shop per year = 8
D Price $1575 Expected number of days in the shop per year = 3.5
E Price $1525 Expected number of days in the shop per year = 2.5
F Price $1245 Expected number of days in the shop per year = 4

The laptop will be an important part of Jonna’s livelihood for the next two years. (After two years, the laptop will have a negligible salvage value.) In fact, Jonna can foresee that there will be specific losses if the laptop is in the shop for repairs. The magnitude of the losses are uncertain but are estimated to be approximately $175 per day that the laptop is down.

a. Can you give any advice to Jonna without doing any calculations? (Maximum four line answer, No calculation, No graph required)
b. Use the information given to determine weights KP and KR, where R stands for ‘reliability’ and P stands for ‘price’.
c. Calculate overall utilities for the laptops, What do you conclude?
d. What consideration other than losses might be important in determining the trade off rate between cost and reliability? List at least three of them.
(Please show all the steps)

Question 2:

QUESTION 2
HELP – THE BETTOR (Calculation required 4 decimal places, Objective: Maximization of wealth)

A utility function is called Linear-plus-exponential when it contains both linear and exponential terms.

Brigg, a bettor, has a choice between the following two alternatives:
(For simplicity it is assumed that cost of each alternative is negligible, equivalent to zero)

Alternative # A 5% chances to WIN $11,900
95% chances to WIN $1200

Alternative # B 90% chances to WIN $2100
10% chances to LOSE $2150

If Brigg has $3,000, having utility function U(x) = ln(x) – 0.0005x, where x is total wealth which Alternative he should choose A or B?

If Brigg has $6,000, having utility function U(x) = ln(x) – 0.0005x, where x is total wealth which Alternative he should choose A or B?

If Brigg has $12,000, having utility function U(x) = 0.0015x -12.48e-x/13420, where x is total wealth which Alternative he should choose A or B?

If bettor is not risk neutral and having utility function U(x) = 1.75 – e-x/13420 what will be your recommendation, Alternative A or B. Calculate Risk premium for Alternative A and B independently? Which Alternative will give high certainty value to Brigg? Assume Brigg is risk neutral, what will be your recommendation among the alternatives?

NOTE :
(MUST calculate at least 4 decimal places otherwise you july not choose correct alternative and marks will be deducted.) (It is advisable to use Excel)

AJ DAVIS is a department store chain, which has many credit customers and wants to find out more information about these customers. A sample of 50 credit customers is selected with data collected on the following five variables:

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AJ DAVIS is a department store chain, which has many credit customers and wants to find out more information about these customers. A sample of 50 credit customers is selected with data collected on the following five variables:
1. LOCATION (Rural, Urban, Suburban)
2. INCOME (in $1,000’s – be careful with this)
3. SIZE (Household Size, meaning number of people living in the household)
4. YEARS (the number of years that the customer has lived in the current location)
5. CREDIT BALANCE (the customers current credit card balance on the store’s credit card, in $).
The data appears below, and is available in Doc Sharing Course Project Data Set as an EXCEL file:
LOCATION INCOME($1000) SIZE YEARS CREDIT BALANCE($)
Urban 54 3 12 4016
Rural 30 2 12 3159
Suburban 32 4 17 5100
Suburban 50 5 14 4742
Rural 31 2 4 1864
Urban 55 2 9 4070
Rural 37 1 20 2731
Urban 40 2 7 3348
Suburban 66 4 10 4764
Urban 51 3 16 4110
Urban 25 3 11 4208
Urban 48 4 16 4219
Rural 27 1 19 2477
Rural 33 2 12 2514
Urban 65 3 12 4214
Suburban 63 4 13 4965
Urban 42 6 15 4412
Urban 21 2 18 2448
Rural 44 1 7 2995
Urban 37 5 5 4171
Suburban 62 6 13 5678
Urban 21 3 16 3623
Suburban 55 7 15 5301
Rural 42 2 19 3020
Urban 41 7 18 4828
Suburban 54 6 14 5573
Rural 30 1 14 2583
Rural 48 2 8 3866
Urban 34 5 5 3586
Suburban 67 4 13 5037
Rural 50 2 11 3605
Urban 67 5 1 5345
Urban 55 6 16 5370
Urban 52 2 11 3890
Urban 62 3 2 4705
Urban 64 2 6 4157
Suburban 22 3 18 3579
Urban 29 4 4 3890
Suburban 39 2 18 2972
Rural 35 1 11 3121
Urban 39 4 15 4183
Suburban 54 3 9 3730
Suburban 23 6 18 4127
Rural 27 2 1 2921
Urban 26 7 17 4603
Suburban 61 2 14 4273
Rural 30 2 14 3067
Rural 22 4 16 3074
Suburban 46 5 13 4820
Suburban 66 4 20 5149

PROJECT PART A: Exploratory Data Analysis

1. Open the file MATH533 Project Consumer.xls from the Course Project Data Set folder in Doc Sharing.
2. For each of the five variables, process, organize, present and summarize the data. Analyze each variable by itself using graphical and numerical techniques of summarization. Use MINITAB as much as possible, explaining what the printout tells you. You july wish to use some of the following graphs: stem-leaf diagram, frequency/relative frequency table, histogram, boxplot, dotplot, pie chart, bar graph. Caution: not all of these are appropriate for each of these variables, nor are they all necessary. More is not necessarily better. In addition be sure to find the appropriate measures of central tendency, and measures of dispersion for the above data. Where appropriate use the five number summary (the Min, Q1, Median, Q3, Max). Once again, use MINITAB as appropriate, and explain what the results mean.
3. Analyze the connections or relationships between the variables. There are ten pairings here (Location and Income, Location and Size, Location and Years, Location and Credit Balance, income and Size, Income and Years, Income and Balance, Size and Years, Size and Credit Balance, Years and Credit Balance). Use graphical as well as numerical summary measures. Explain what you see. Be sure to consider all 10 pairings. Some variables show clear relationships, while others do not.
4. Prepare your report in Microsoft Word, integrating your graphs and tables with text explanations and interpretations. Be sure that you have graphical and numerical back up for your explanations and interpretations. Be selective in what you include in the report. I’m not looking for a 20 page report on every variable and every possible relationship (that’s 15 things to do). Rather what I want you do is to highlight what you see for three individual variables (no more than 1 graph for each, one or two measures of central tendency and variability (as appropriate), and two or three sentences of interpretation). For the 10 pairings, identify and report only on three of the pairings, again using graphical and numerical summary (as appropriate), with interpretations. Please note that at least one of your pairings must include Location and at least one of your pairings must not include Location.
• All DeVry University policies are in effect, including the plagiarism policy.
• Project Part A report is due by the end of Week 2.
• Project Part A is worth 100 total points. See grading rubric below.
Submission: The report from part 4 including all relevant graphs and numerical analysis along with interpretations.
Format for report:
A. Brief Introduction
B. Discuss your 1st individual variable, using graphical, numerical summary and interpretation
C. Discuss your 2nd individual variable, using graphical, numerical summary and interpretation
D. Discuss your 3rd individual variable, using graphical, numerical summary and interpretation
E. Discuss your 1st pairing of variables, using graphical, numerical summary and interpretation
F. Discuss your 2nd pairing of variables, using graphical, numerical summary and interpretation
G. Discuss your 3rd pairing of variables, using graphical, numerical summary and interpretation
H. Conclusion

Which type of model is used to help managers estimate future conditions and sales figures resulting from these conditions?

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Which type of model is used to help managers estimate future conditions
and sales figures resulting from these conditions?
a. Forecasting
b. Predictive
c. Statistical
d. Sensitivity analysis

I would like for each of you to envision a type of fraud that you would like to investigate. Examples might include fictitious employees, bogus travel claims, etc. Envision a sample you would take to examine that fraud.

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“”I would like for each of you to envision a type of fraud that you would like to investigate. Examples might include fictitious employees, bogus travel claims, etc. Envision a sample you would take to examine that fraud. Discuss what the type of fraud, the population you would sample and what would be the sampling unit. In your example, do you see any challenges in sampling?

word limit 500″”

Below is a set of data which you are to plot. Then tell me how many pay structures and what jobs should be included in the pay structure(s).

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Below is a set of data which you are to plot. Then tell me how many pay structures and what jobs should be included in the pay structure(s). In your answer you are to show me the plot as well. 

Job Evaluation Points Salary Survey
A 80 $12.95
B 80 $13.00
C 100 $13.20
D 105 $13.15
E 108 $13.50
F 115 $13.80
G 140 $14.55
H 150 $15.00
I 160 $15.45
J 190 $16.35
K 195 $16.50
L 203 $21.00
M 215 $17.25
N 218 $17.40
O 250 $18.45
P 255 $18.60
Q 275 $19.10
R 300 $19.80
S 310 $20.00
T 360 $25.00
U 365 $26.25
V 370 $26.50
W 390 $28.00

What are the two basic laws of probability?

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What are the two basic laws of probability?

What is seasonality, and what role does it play in regression analysis? 200 Words

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What is seasonality, and what role does it play in regression analysis? 200 Words

Construct a c-chart for test errors, and set the control limits to contain 99.73% of the random variation in test scores. What does the chart tell you? Has the new math program been effective?

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The school board is trying to evaluate a new math program introduced to second-graders in five elementary schools across the county this year. A sample of the student scores on standardized math tests in each elementary school yielded the following data:

School No. of Test Errors
A 52
B 27
C 35
D 44
E 55

Construct a c-chart for test errors, and set the control limits to contain 99.73% of the random variation in test scores. What does the chart tell you? Has the new math program been effective?

Why is linear regression more appropriate for long-range forecasts?

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Why is linear regression more appropriate for long-range forecasts?

What is seasonality, and what role does it play in regression analysis?
200 words

Develop three regression models to predict the selling price based upon each of the other factors individually. Which of these is best?

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1) The following data give the selling price, square footage, number of bedrooms, and age of houses that have sold in a neighborhood in the past 6 months. Develop three regression models to predict the selling price based upon each of the other factors individually. Which of these is best?

SELLING PRICE ($) SQUARE FOOTAGE BEDROOMS AGE (YEARS)
64,000 1,670 2 30
59,000 1,339 2 25
61,500 1,712 3 30
79,000 1,840 3 40
87,500 2,300 3 18
92,500 2,234 3 30
95,000 2,311 3 19
113,000 2,377 3 7
115,000 2,736 4 10
138,000 2,500 3 1
142,500 2,500 4 3
144,000 2,479 3 3
145,000 2,400 3 1
147,500 3,124 4 0
144,000 2,500 3 2
155,500 4,062 4 10
165,000 2,854 3 3

the business question there are two other follow up questions that i will post whenever you would like me to.

Please do the work in excel so that i can understand the calculations.

The school board is trying to evaluate a new math program introduced to second-graders in five elementary schools across the county this year.

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The school board is trying to evaluate a new math program introduced to second-graders in five elementary schools across the county this year. A sample of the student scores on standardized math tests in each elementary school yielded the following data:

School No. of Test Errors
A 52
B 27
C 35
D 44
E 55

Construct a c-chart for test errors, and set the control limits to contain 99.73% of the random variation in test scores. What does the chart tell you? Has the new math program been effective?

Identify the slope and y intercept of the line.

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Below is the regression output for the relationship between 2007 and 2008 median home prices for the largest cities in the US. Both variables were in thousands of dollars

Linear regression results:
Dependent Variable: 2008 median home prices
Independent Variable: 2007 median home prices
Y= 48.9 + 0.67X
R (correlation coefficient) = 0.9549
R-sq = 0.911793

A. Use the regression equation to predict the 2008 median home price for a city whose 2007 median
home price was $300,000.

B. Identify the slope and y intercept of the line.