Questions
A standard deck of 52 cards is shuffled and dealt. Let X1 be the number of...

A standard deck of 52 cards is shuffled and dealt. Let X1 be the number of cards appearing before the first ace, X2 the number of cards between the first and second ace (not counting either ace), X3 the number between the second and third ace, X4 the number between the third and forth ace, and X5 the number after the last ace. It can be shown that each of these random variables Xi had the same distribution, i=1,2,...,5, and you can assume this to be true.

a) Write down a formula for P(Xi=k), 0≤k≤48

b) Show that E(Xi)= 9.6 (Hint:Don't use your answer to part a)

c) Are X1,X2,...,X5 pairwise independent? Prove your answer.

In: Math

Download the dataset CARS1 from BlackBoard. a. Do not worry about outliers. Assume the data is...

Download the dataset CARS1 from BlackBoard. a. Do not worry about outliers. Assume the data is correct and any outliers will remain in the dataset. b. Do scatterplot and analyze the results. c. Test for correlation (correlation coefficient) d. Regress weight (column 2) against gas mileage in the city (column 1). Make sure you make gas mileage the dependent (Y) variable. e. Determine and fully explain R2 MPG City Weight 19 3545 23 2795 23 2600 19 3515 23 3245 17 3930 20 3115 22 3235 17 3995 22 3115 23 3240 17 4020 18 3220 19 3175 20 3450 19 3225 17 3985 32 2440 29 2500 28 2290

In: Math

Engineers at the American Lighting Company recently developed a new three-way light bulb that they say...

Engineers at the American Lighting Company recently developed a new three-way light bulb that they say is more energy efficient than the company’s existing three-way light bulb. The also claim that the bulb will outlast the current bulb, which has an average lifetime of 700 hours. The standard deviation (σ) for the lifetime of bulbs is 75 hours. The American Lighting Company has decided that before it begins full scale production on the new light bulbs it should take a sample of 225 bulbs and determine whether the mean life of the new bulb exceeds the old bulb’s 700 hours. The sample of 225 bulbs gave a sample mean of 704 hours. Assuming a significance level of .05 perform all hypothesis testing steps. Does the sample support the claim that the average lifetime of the new bulb is longer?

In: Math

In the healthy handwashing survey, it was found the 64% of adult Americans operate the flusher...

In the healthy handwashing survey, it was found the 64% of adult Americans operate the flusher of toilets in public restrooms with their foot. Suppose you survey a random sample of 740 adult American women aged 18-24 years. Use normal approximation to the binomial to approximate the probability of following.

a) check the conditions for normal distribution approximation

c)determine probability of exactly 500 of those surveyed flush toilets in public restrooms with their foot.

d) determine probability of no more than 490 of those surveyed flush toilets in public restrooms with their foot.

In: Math

Poissson distribution In order to control the polishing quality of a lens, a certain company is...

Poissson distribution

In order to control the polishing quality of a lens, a certain company is used to finish the number of spots on the surface considering the defective lens if 3 or more spots appear on it. The average rate is 2 defects per cm2. Calculate the probability that a 4cm2 lens will not be classified as defective.

In: Math

The health of the bear population in a park is monitored by periodic measurements taken from...

The health of the bear population in a park is monitored by periodic measurements taken from anesthetized bears. A sample of the weights of such bears is given below. Find a​ 95% confidence interval estimate of the mean of the population of all such bear weights. The​ 95% confidence interval for the mean bear weight is the following.

data table 80 344 416 348 166 220 262 360 204 144 332 34 140 180

In: Math

We are attempting to see if we can justify the additional expense of premium fuel over...

We are attempting to see if we can justify the additional expense of premium fuel over economy; i.e., we will only use premium fuel if we are convinced that it actually helps mpg. For each of the 25 cars at our disposal, we randomly picked one fuel to use first, drove the car until nearly empty, and calculated mpg when refilling the tank. We then filled it with the other fuel, repeating the process, obtaining mpg for that fuel, driving over the same roads.  

Explain why it would be important to randomize the order in which we test two gasoline types. Give a specific example of how not randomizing might cause a problem with this design.




In: Math

PART 1: Determining the Appropriate Test Assume that the following three questions appeared on a survey...

PART 1: Determining the Appropriate Test

Assume that the following three questions appeared on a survey that is being used to collect data on consumer behavior for your company.

Question 1:         Do you subscribe to Netflix? (Circle One)                               YES         NO

Question 2:         What is your monthly average income in dollars?               $__________

Question 3:         In which of the 5 U.S. regions do you reside? (Circle one)

                                Northeast           Southwest          West          Midwest        Southeast

                               

  1. You want to determine if a relationship exists between the U.S. region in which the consumer resides and whether or not they are a subscriber to Netflix.

  1. Which test should you run to help you answer this question? (ANOVA or Chi-Square test)

  1. Given your answer in part “A” above, set up the null and alternative hypotheses to begin your test.

  1. Now assume that you want to determine if the average monthly income of a consumer is different among groups of people living in different regions of the United States.

  1. Which test should you run to help you answer this question? (ANOVA or Chi-Square test)
  1. Given your answer in part “A” above, set up the null and alternative hypotheses to begin your test.

PART 2: Analysis of a Chi-Square test

Assume that a research study was conducted that included the following survey questions:

Question 1:         Have you ever attended an event at the city Performing Arts Center?       YES         NO

Question 2:         Have you ever attended an event at the city Athletic Center?                       YES         NO

A sample of 93 people answered the survey questions. The research team utilized Minitab statistical software to create the results shown below. You will find a contingency table with the Chi-Square test statistic and p-value at the bottom.

---------------------------------------------------------------------------------------------------------------------------------

CHI-SQUARE TEST FOR ASSOCIATION: PERFORMING ARTS CENTER ATTENDANCE, ATHLETIC CENTER ATTENDANCE

Rows: Performing Arts Center Attendance                        Columns: Athletic Center Attendance

NO

YES

   All

NO

15

1

16

9.634

6.366

YES

41

36

77

46.366

30.634

All

56

37

93

Cell Contents:                        Count

                                                Expected Count   

Chi-Square

DF

P-Value

Pearson

9.072

1

0.003

Review the study and the Minitab results. Then answer the following questions:

  1. If you want to determine if a relationship exists between whether or not a person attended an event at the Performing Arts center and whether or not the person attended an event at the Athletic Center, set up the null and alternative hypotheses to begin your test.
  1. Find the p-value in the output. Draw a conclusion about your hypotheses based on this p-value. Be sure to explain your answer. Why did you draw the conclusion that you did?

In: Math

The next two questions (7 and 8) refer to the following: The weight of bags of...

The next two questions (7 and 8) refer to the following:

The weight of bags of organic fertilizer is normally distributed with a mean of 60 pounds and a standard deviation of 2.5 pounds.

7. What is the probability that a random sample of 33 bags of organic fertilizer has a total weight between 1963.5 and 1996.5 pounds?

8. If we take a random sample of 9 bags of organic fertilizer, there is a 75% chance that their mean weight will be less than what value? Keep 4 decimal places in intermediate calculations and report your final answer to 4 decimal places.

The next two questions (8 and 9) refer to the following:

Question 10 and 11

Suppose that 40% of students at a university drive to campus.

10. If we randomly select 100 students from this university, what is the approximate probability that less than 35% of them drive to campus?

Keep 6 decimal places in intermediate calculations and report your final answer to 4 decimal places.

11. If we randomly select 100 students from this university, what is the approximate probability that more than 50 of them drive to campus?

Keep 6 decimal places in intermediate calculations and report your final answer to 4 decimal places.

12. Suppose that IQs of adult Canadians follow a normal distribution with standard deviation 15. A random sample of 30 adult Canadians has a mean IQ of 112.

We would like to construct a 97% confidence interval for the true mean IQ of all adult Canadians. What is the critical value z* to be used in the interval? (You do not need to calculate the calculate the confidence interval. Simply find z*. Input a positive number since we always use the positive z* value when calculating confidence intervals.)

Report your answer to 2 decimal places.

In: Math

Components of a certain type are shipped to a supplier in batches of ten. Suppose that...

Components of a certain type are shipped to a supplier in batches of ten. Suppose that 51% of all such batches contain no defective components, 33% contain one defective component, and 16% contain two defective components. Two components from a batch are randomly selected and tested. What are the probabilities associated with 0, 1, and 2 defective components being in the batch under each of the following conditions? (Round your answers to four decimal places.)

(a) Neither tested component is defective.

no defective components :

one defective component :

two defective components :

(b) One of the two tested components is defective. [Hint: Draw a tree diagram with three first-generation branches for the three different types of batches.]

no defective components :

one defective component :

two defective components :

In: Math

The FBI wants to determine the effectiveness of their 10 Most Wanted list. To do so,...

The FBI wants to determine the effectiveness of their 10 Most Wanted list. To do so, they need to find out the fraction of people who appear on the list that are actually caught.

Step 2 of 2 :  

Suppose a sample of 362 suspected criminals is drawn. Of these people, 119 were captured. Using the data, construct the 90% confidence interval for the population proportion of people who are captured after appearing on the 10 Most Wanted list. Round your answers to three decimal places.

In: Math

*Repeated Measures Analysis of Variance* Examining differences between groups on one or more variables / same...

*Repeated Measures Analysis of Variance*
Examining differences between groups on one or more variables / same participants being tested more than once / with more than two groups.

What test and method would be used to examine the difference between male and female users considering the different variable (Pain Reliever, Sedative, Tranquilizer & Stimulant)

Create a graph illustration.

Describe the Graph.

TABLE 1.22A, Misuse separated by age and 2016, 2017
Age Misuse_2016 Misuse_2017
12 66 55
13 90 105
14 160 127
15 253 234
16 322 295
17 426 415
18 537 466
19 631 503
20 692 671
21 700 661
22 659 728
23 581 660
24 648 681
25 577 585
AGE PR2016 PR2017 TR2016 TR2017 STIM2016 STIM2017 SED2016 SED2017
12 49 40 12 6 6 7 5 74
13 78 78 8 23 11 23 8 55
14 111 84 37 48 47 38 15 15
15 192 152 92 69 74 83 19 12
16 196 188 122 132 96 98 25 18
17 255 226 162 181 193 202 28 18
18 259 233 232 184 254 229 21 17
19 272 236 271 209 313 259 40 25
20 303 304 255 252 431 352 22 14
21 341 317 226 228 376 397 42 35
22 301 353 221 282 355 407 16 22
23 281 334 234 245 284 323 37 18
24 369 365 214 278 302 316 43 44
25 327 318 193 202 263 264 34 25
Misuse of Prescription Drugs, Gender, Age
Table 1.53A PAIN RELIEVERS (DEMOGRAPHICS)
Gender 12-17(16) 12-17(17) 18-25(16) 18-25(17) Total
Male 413 342 1328 1263 3,346
Female 469 425 1126 1197 3217
Table 1.57A TRANQUILIZERS (DEMOGRAPHICS)
Gender 12-17(16) 12-17(17) 18-25(16) 18-25(17) Total
Male 203 227 914 1004 2,348
Female 231 231 930 877 2269
Table 1.60A STIMULANTS (DEMOGRAPHICS)
Gender 12-17(16) 12-17(17) 18-25(16) 18-25(17) Total
Male 243 238 1377 1474 3,332
Female 184 214 1201 1071 2670
Table 1.63A SEDATIVES (DEMOGRAPHICS)
Gender 12-17(16) 12-17(17) 18-25(16) 18-25(17) Total
Male 39 41 114 105 299
Female 61 32 141 94 328

In: Math

Workers in several industries were surveyed to determine the proportion of workers who feel their industry...

Workers in several industries were surveyed to determine the proportion of workers who feel their industry is understaffed. In the government sector, 37% of the respondents said they were understaffed, in the health care sector 33% said they were understaffed and in the education sector 28% said they were understaffed (USA Today, January 11, 2010). Suppose that 200 workers were surveyed in each industry.

b) Assuming the same sample size will be used in each industry, how large would the sample need to be to ensure that the margin of error is 5% or less for each of the three confidence intervals? Perform the calculation using an appropriate pilot study proportion as well as a worst case scenario.

In: Math

Determine and interpret the linear correlation coefficient, and use linear regression to find a best fit...

Determine and interpret the linear correlation coefficient, and use linear regression to find a best fit line for a scatter plot of the data and make predictions. Scenario According to the U.S. Geological Survey (USGS), the probability of a magnitude 6.7 or greater earthquake in the Greater Bay Area is 63%, about 2 out of 3, in the next 30 years. In April 2008, scientists and engineers released a new earthquake forecast for the State of California called the Uniform California Earthquake Rupture Forecast (UCERF). As a junior analyst at the USGS, you are tasked to determine whether there is sufficient evidence to support the claim of a linear correlation between the magnitudes and depths from the earthquakes. Your deliverables will be a PowerPoint presentation you will create summarizing your findings and an excel document to show your work. Concepts Being Studied • Correlation and regression • Creating scatterplots • Constructing and interpreting a Hypothesis Test for Correlation using r as the test statistic You are given a spreadsheet that contains the following information: • Magnitude measured on the Richter scale • Depth in km Using the spreadsheet, you will answer the problems below in a PowerPoint presentation. What to Submit The PowerPoint presentation should answer and explain the following questions based on the spreadsheet provided above. • Slide 1: Title slide • Slide 2: Introduce your scenario and data set including the variables provided. • Slide 3: Construct a scatterplot of the two variables provided in the spreadsheet. Include a description of what you see in the scatterplot. • Slide 4: Find the value of the linear correlation coefficient r and the critical value of r using α = 0.05. Include an explanation on how you found those values. • Slide 5: Determine whether there is sufficient evidence to support the claim of a linear correlation between the magnitudes and the depths from the earthquakes. Explain. • Slide 6: Find the regression equation. Let the predictor (x) variable be the magnitude. Identify the slope and the y-intercept within your regression equation. • Slide 7: Is the equation a good model? Explain. What would be the best predicted depth of an earthquake with a magnitude of 2.0? Include the correct units. • Slide 8: Conclude by recapping your ideas by summarizing the information presented in context of the scenario. Along with your PowerPoint presentation, you should include your Excel document which shows all calculations.

MAG DEPTH
0.70 7.2
0.74 2.2
0.64 13.9
0.39 15.5
0.70 3.0
2.20 2.4
1.98 14.4
0.64 5.7
1.22 6.1
0.20 9.1
1.64 17.2
1.32 8.7
2.95 9.3
0.90 12.3
1.76 7.4
1.01 7.0
1.26 17.1
0.00 8.8
0.65 6.0
1.46 19.1
1.62 12.7
1.83 4.7
0.99 8.6
1.56 6.0
0.40 14.6
1.28 4.9
0.83 19.1
1.34 9.9
0.54 16.1
1.25 4.6
0.92 4.9
1.00 16.1
0.79 14.0
0.79 4.2
1.44 5.9
1.00 5.4
2.24 15.6
2.50 7.7
1.79 15.4
1.25 16.4
1.49 4.9
0.84 8.1
1.42 7.5
1.00 14.1
1.25 11.1
1.42 16.0
1.35 5.5
0.93 7.3
0.40 3.1
1.39

6.0

In: Math

The table below summarizes baseline characteristics of patients participating in a clinical trial. a) Are there...

The table below summarizes baseline characteristics of patients participating in a clinical trial. a) Are there any statistically significant differences in baseline characteristics between treatment groups? Justify your answer.

b) Write the hypotheses and the test statistic used to compare ages between groups. (No calculations – just H0, H1 and form of the test statistic).

c) Write the hypotheses and the test statistic used to compare % females between groups. (No calculations – just H0, H1 and form of the test statistic).

d) Write the hypotheses and the test statistic used to compare % females between groups. (No calculations – just H0, H1 and form of the test statistic.) Characteristic Placebo (n = 125) Experimental ( n =125) P Mean (+ SD) Age 54 + 4.5 53 + 4.9 0.7856 % Female 39% 52% 0.0289 % Less than High School Education 24% 22% 0.0986 % Completing High School 37% 36% % Completing Some College 39% 42% Mean (+ SD) Systolic Blood Pressure 136 + 13.8 134 + 12.4 0.4736 Mean (+ SD) Total Cholesterol 214 + 24.9 210 + 23.1 0.8954 % Current Smokers 17% 15% 0.5741 % with Diabetes 8% 3% 0.0438

In: Math