1. The daily temperature in August in a region is normally distributed with a mean of 86 degrees F and a standard deviation of 4 degrees F. What is the probability (4 significant figures) that a daily temperature would be 72 degrees F or less? Would this be considered unusual, or not unusual?

2. The daily temperature in August in a region is normally distributed with a mean of 86 degrees F and a standard deviation of 4 degrees F. What is the probability that a daily temperature would be between 90 and 100 degrees F? Would such temperatures be considered unusual, or not unusual?

3. The daily temperature in August in a region is normally distributed with a mean of 86 degrees F and a standard deviation of 4 degrees F. What is the 90th percentile for all such daily temperatures? Round to the nearest hundredth of a degree; don't forget units of measure

4. The daily temperature in August in a region is normally distributed with a mean of 86 degrees F and a standard deviation of 4 degrees F. What is the centered, symmetric interval containing 80% of all such temperatures? (round to the nearest hundredth of a degree); don't forget units of measure

A marketing company based out of New York City is doing well and is looking to expand internationally. The CEO and VP of Operations decide to enlist the help of a consulting firm that you work for, to help collect data and analyze market trends.

You work for Mercer Human Resources. The Mercer Human Resource Consulting website (www.mercer.com) lists prices of certain items in selected cities around the world. They also report an overall cost-of-living index for each city compared to the costs of hundreds of items in New York City (NYC). For example, London at 88.33 is 11.67% less expensive than NYC.

More specifically, if you choose to explore the website further you will find a lot of fun and interesting data. You can explore the website more on your own after the course concludes.

https://mobilityexchange.mercer.com/Insights/cost-of-living-rankings#rankings

In the Excel document, you will find the 2018 data for 17 cities in the data set Cost of Living. Included are the 2018 cost of living index, cost of a 3-bedroom apartment (per month), price of monthly transportation pass, price of a mid-range bottle of wine, price of a loaf of bread (1 lb.), the price of a gallon of milk and price for a 12 oz. cup of black coffee. All prices are in U.S. dollars.

You use this information to run a Multiple Linear Regression to predict Cost of living, along with calculating various descriptive statistics. This is given in the Excel output (that is, the MLR has already been calculated. Your task is to interpret the data). Based on this information, in which city should you open a second office in? You must justify your answer. If you want to recommend 2 or 3 different cities and rank them based on the data and your findings, this is fine as well. This should be ¾ to 1 page, no more than 1 single-spaced page in length, using 12-point Times New Roman font. You do not need to do any calculations, but you do need to pick a city to open a second location at and justify your answer based upon the provided results of the Multiple Linear Regression. Think of this assignment as the first page of a much longer report, known as an Executive Summary, that essentially summarizes your findings briefly and at a high level. This needs to be written up neatly and professionally. This would be something you would present at a board meeting in a corporate environment.

City Cost of Living Index Rent (in City Centre) Monthly Pubic Trans Pass Loaf of Bread Milk Bottle of Wine (mid-range) Coffee

Mumbai 31.74 $1,642.68 $7.66 $0.41 $2.93 $10.73 $1.63

Prague 50.95 $1,240.48 $25.01 $0.92 $3.14 $5.46 $2.17

Warsaw 45.45 $1,060.06 $30.09 $0.69 $2.68 $6.84 $1.98

Athens 63.06 $569.12 $35.31 $0.80 $5.35 $8.24 $2.88

Rome 78.19 $2,354.10 $41.20 $1.38 $6.82 $7.06 $1.51

Seoul 83.45 $2,370.81 $50.53 $2.44 $7.90 $17.57 $1.79

Brussels 82.2 $1,734.75 $57.68 $1.66 $4.17 $8.24 $1.51

Madrid 66.75 $1,795.10 $64.27 $1.04 $3.63 $5.89 $1.58

Vancouver 74.06 $2,937.27 $74.28 $2.28 $7.12 $14.38 $1.47

Paris 89.94 $2,701.61 $85.92 $1.56 $4.68 $8.24 $1.51

Tokyo 92.94 $2,197.03 $88.77 $1.77 $6.46 $17.75 $1.49

Berlin 71.65 $1,695.77 $95.34 $1.24 $3.52 $5.89 $1.71

Amsterdam 85.9 $2,823.28 $105.93 $1.33 $4.34 $7.06 $1.71

New York 100 $5,877.45 $121.00 $2.93 $3.98 $15.00 $0.84

Sydney 90.78 $3,777.72 $124.55 $1.94 $4.43 $14.01 $2.26

Dublin 87.93 $3,025.83 $144.78 $1.37 $4.31 $14.12 $2.06

London 88.33 $4,069.99 $173.81 $1.23 $4.63 $10.53 $1.90

mean 75.49 $2,463.12 $78.01 $1.47 $4.71 $10.41 $1.76

median 82.2 $2,354.10 $74.28 $1.37 $4.34 $8.24 $1.71

min 31.74 $569.12 $7.66 $0.41 $2.68 $5.46 $0.84

max 100 $5,877.45 $173.81 $2.93 $7.90 $17.75 $2.88

Q1 66.75 $1,695.77 $41.20 $1.04 $3.63 $7.06 $1.51

Q3 88.33 $2,937.27 $105.93 $1.77 $5.35 $14.12 $1.98

New York 100 $5,877.45 $121.00 $2.93 $3.98 $15.00 $0.84

SUMMARY OUTPUT

Regression Statistics

Multiple R 0.935824078

R Square 0.875766706

Adjusted R Square 80.12%

Standard Error 8.30945321

Observations 17

ANOVA

df SS MS F Significance F

Regression 6 4867.380768 811.2301279 11.74895331 0.00049963

Residual 10 690.4701265 69.04701265

Total 16 5557.850894

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%

Intercept  35.63950178 15.41876933 2.311436213 0.043401141 1.284342794 69.99466077 1.284342794 69.99466077

Rent (in City Centre) -0.003212852 0.003974813 -0.808302603 0.437722785 -0.012069287 0.005643584 -0.012069287 0.005643584

Monthly Pubic Trans Pass 0.299650003 0.076964051 3.89337619 0.002993072 0.128163411 0.471136595 0.128163411 0.471136595

Loaf of Bread 16.59481787 6.713301249 2.47193106 0.032995588 1.636650533 31.55298521 1.636650533 31.55298521

Milk 2.912081706 1.98941146 1.463790555 0.173964311 -1.520603261 7.344766672 -1.520603261 7.344766672

Bottle of Wine (mid-range) -0.889805486 0.740190296 -1.202130709 0.257006081 -2.539052244 0.759441271 -2.539052244 0.759441271

Coffee -2.527438053 6.484555358 -0.389762738 0.704884259 -16.97592778 11.92105168 -16.97592778 11.92105168

RESIDUAL OUTPUT

Observation Predicted Cost of Living Index Residuals Standard Residuals City

1 34.32607137 -2.586071368 -0.39366613 Mumbai

2 53.21656053 -2.266560525 -0.345028417 Prague

3 49.41436121 -3.964361215 -0.603477056 Warsaw

4 58.63611785 4.42388215 0.673427882 Athens

5 73.08449538 5.105504624 0.777188237 Rome

6 86.50256003 -3.052560026 -0.464677621 Seoul

7 75.89216916 6.307830843 0.960213003 Brussels

8 67.7257781 -0.975778105 -0.148538356 Madrid

9 90.51996071 -16.45996071 -2.50562653 Vancouver

10 81.07358731 8.866412685 1.349694525 Paris

11 83.80564633 9.134353675 1.390481989 Tokyo

12 80.02510391 -8.37510391 -1.274904778 Berlin

13 82.41624318 3.483756815 0.530316788 Amsterdam

14 97.75654811 2.243451893 0.341510693 New York

15 87.73993924 3.040060757 0.462774913 Sydney

16 86.81668291 1.11331709 0.169475303 Dublin

17 94.36817468 -6.038174677 -0.919164446 London

Can someone explain a,b and c? The answers are correct I believe but I just need a more clear explenation on the formulas and final answers

If 2 cards are drawn from a well-shuffled deck of 52 playing cards, what are the probabilities of getting

Answer:

Total no of ways of drawing 2 cards from a well-shuffled deck of 52 playing cards = ⁵²C₂ = 1326

(a)        two spades;

Number of ways getting 2 spades / total number of ways = (¹³C₂)/1326 = 78/1326 = 0.0588

(b)        two aces;

Number of ways getting 2 aces / total number of ways = (⁴C₂)/1326 = 4/1326 = 0.003

(c)        a king and a queen?

            13*13/1326 = 0.12745

A psychologist is interested in the conditions that affect the number of dreams per month that people report in which they are alone. We will assume that based on extensive previous research, it is known that in the general population the number of such dreams per month follows a normal curve, with μ= Unknown node type: span and σ=4 . The researcher wants to test the prediction that the number of such dreams will be greater among people who have recently experienced a traumatic event. Thus, the psychologist studies 36 individuals who have recently experienced a traumatic event, having them keep a record of their dreams for a month. Their mean number of alone dreams is 8. Should you conclude that people who have recently had a traumatic experience have a significantly different number of dreams in which they are alone? (a) Carry out a Z test using the five steps of hypothesis testing (use the .05 level). (b) Make a drawing of the distributions involved. (c) Explain your answer to a person who has never had a course in statistics. (d) ADVANCED TOPIC: Figure the 95% confidence interval.

1. The association between the variables "dollars earned" and "hours worked" for a worker at store would be

QUESTION 2

The association between the variables "GPA" and "hours spent studying" for a student would usually be

QUESTION 3

The association between the variables "cost of a book" and "the buyers body temperature" would be

QUESTION 4

The association between the variables "airfare" and "distance to destination" would be

QUESTION 5

A graph that will help to one to see what type of curve might best fit the bivariate data

QUESTION 6

If the correlation coefficient for a linear regression is -0.932. there is sufficient evidence that a linear relationship exists between the x and y data

QUESTION 7

Which of the following correlation coefficients represents the most linear function?

QUESTION 8

If the correlation coefficient for linear regression is 0.25. there is sufficient evidence that a linear relationship exists between the x and y data

QUESTION 9

A data point that lies statistically far from the regression line is a potential

QUESTION 10

1. correlation5:
   
   If the correlation coefficient is 0.90, the value of the coefficient of determination would be

QUESTION 11

Use your TI83 to determine the correlation coefficient of the following set of points. Round correctly to the nearest hundredth.

(4, 4), (-2, -7), (3, 3), (4, -1)

QUESTION 12

Use your TI83 to determine the correlation coefficient of the following set of points. Round correctly to the nearest hundredth.

(4, 4), (-2, -4), (7, -2), (4, 1)

QUESTION 13

Use your TI83 to determine the correlation coefficient of the following set of points. Round correctly to the nearest hundredth.

(2, 4), (1, -1), (2, 2), (5, -4)

As a part of a new healthcare reform, hospitals must report incidence of specific demographic and health care outcomes to maintain funding. Within this report, it was found that 23.3% the Medicare population in Westmoreland county is Diabetic. As part of a random survey to determine if current preventative measures are helping to target this, a random sample of 50 individuals within the Medicare population we sampled.

Let X be the number of individuals who are Diabetic.

1. Can X be considered a binomially distributed random variable? Why?

2. Identify n and p for this problem.

3. Can variables X be well-approximated by normal random variables?

4. What is the expected number of diabetic individuals for this problem?

5. What is the variance for the number of diabetic individuals for this problem?

6. How many combinations are possible that consists of exactly 20 people that are diabetic?

7. What is the probability of observing 20 diabetic individuals?

Describe how simple linear regression analysis and multiple regression are used to support areas of industry research, academic research, and scientific research.

1. A sample of eight resistors of a certain type resulted as follows:

                  43, 46, 42, 38, 40, 46, 49, 40

Compute the following:

1. Sample Mean
2. Sample Variance
3. Sample Median
4. 25% Percentile
5. 75% Percentile

2. Consider the following pdf:

      P(X = 0) = 0.48, P(X = 1) = 0.39, P(X = 2) = 0.12, and P(X = 3) = 0.01.

Find the following:

• Do the plot for P(X) and F(X)
• F(0) = P(X ≤ 0) =
• F(1) = P(X ≤ 1) =
• F(2) = P(X ≤ 2) =
• F(3) = P(X ≤ 3) =
• P(1 ≤ X ≤ 2) =
• μ_x =
• σ_x² =

7 people are selected for a survey. Each person is asked about - their opinion on candidate C (Favor or Oppose), and - their political affiliation (Democratic, Independent, or Republican). How many outcomes are in the event that at least one of the 7 people is independent?

Consider a sample with data values of 26, 24, 23, 18, 31, 35, 29, and 24. Compute the range, interquartile range, variance, and standard deviation

Suppose we have data from a health survey conducted in year 2000. Data were obtained from a random sample of 1000 persons.

An OLS linear regression analysis was carried out in the following way:

Dependent Variable: Systolic blood pressure (SBP, in mmHg)

Independent Variables: Gender (1 if female, 0 if male)

Age (in years)

Education (binary variables for “Not graduated from high school” and “Graduated from high school (but not from college)”; the reference category is “Graduated from college”)

A part of the results is shown below. The column labeled “Beta” show estimated values of partial regression coefficients. (It can be interpreted that beta’s for the reference categories, “Male” and “Graduated from college”, are fixed to be zero.) The p-values are for the two-sided test.

1. According to the results of this regression analysis, how much expected difference in systolic blood pressure (in mmHg) is estimated:

1-1. between the two education categories, “Not graduated from high school” and “Graduated from college”, controlling for gender and age (i.e., among those who have the same gender and at the same age)?

1-2. between males and females, controlling for age and education?

2. Suppose we change the reference category of education from “Graduated from college” to “Graduated from high school” and do the same regression analysis again.

What will be the value of partial regression coefficient (beta) for “Not graduated from high school”?

(Hint: The expected SBP differences among the education categories do not change.)

Choose a population that you would plan to sample or survey. Your discussion board thread title should be "Sampling from ______". Some ideas for populations to take a sample from:

Mesa students

San Diego community college students

All San Diego college students

Adults in San Diego

Starbucks customers

Your choice!

Describe an perfect scenario sampling method: Describe in your own words one of the sampling methods learned in class and how it could be applied to your population - in this case, you can assume you will have access to things like a list of everyone living in San Diego.

Describe a realistic sampling method. Being that you don't actually have a list of all San Diego residents (or similar for your population), how would YOU go about trying to get a representative sample? No need to use any fancy terms or definitions here, just describe how you'd collect data from 100 people for your sample.

What are some limitations that will arise with your realistic scenario? Are there groups that might be left out?

Answer all of this in Approximately 150-200 words in length and well-written.

You manage an ice cream factory that makes two flavors: Creamy Vanilla and Continental Mocha. Into each quart of Creamy Vanilla go 2 eggs and 3 cups of cream. Into each quart of Continental Mocha go 1 egg and 3 cups of cream. You have in stock 500 eggs and 900 cups of cream. You make a profit of $3 on each quart of Creamy Vanilla and $2 on each quart of Continental Mocha. How many quarts of each flavor should you make to earn the largest profit?

In a lottery 5 different numbers are chosen from the first 90 positive integers.

(a) How many possible outcomes are there? (An outcome is an unordered sample of five numbers.)

(b) How many outcomes are there with the number 1 appearing among the five chosen numbers?

(c) How many outcomes are there with two numbers below 50 and three numbers above 60?

(d) How many outcomes are there with the property that the last digits of all five numbers are different? (The last digit of 5 is 5 and the last digit of 34 is 4.)

In an article in the Journal of Management, Joseph Martocchio studied and estimated the costs of employee absences. Assume an infinite population. The mean amount of paid time lost during a three-month period was 1.0 day per employee with a standard deviation of 1.4 days. The mean amount of unpaid time lost during a three month period was 1.2 days per employee with a standard deviation of 1.6 days. Suppose we randomly select a sample of 100 blue-collar workers.

1. What is the probability that the average amount of paid time lost during a three-month period for the 100 blue-collar workers will exceed 1.5 days?

2. What is the probability that the average amount of unpaid time lost during a three-month period for the 100 blue-collar workers will be between 1.4 and 1.5 days? Please give a precise explanation, as if you are telling someone who doesn’t know anything about statistics, for the reasoning behind your answer?

3. How large a random sample is needed to construct a 95 percent confidence interval for the mean for population paid time lost with a margin of error equal to 0.1? Please give a precise explanation, as if you are telling someone who doesn't know anything about statistics for the reasoning behind your answer.