Show all work please, due 08/02

For a sample of 10 individuals, a researcher calculates residuals for the relationship between “number of delinquent friends” and “number of prior arrests” and finds that the positive residuals = 125.  The researcher then collects a second sample of 10 individuals and calculates the residuals on the same two variables and discovers the sum of the positive residuals = 75.  What can you conclude about the strength of the relationship between “number of delinquent peers” and “number of prior arrests” across these two random samples?  How are they similar/different?

7. A box contains 12 white marbles and 5 black marbles. Suppose we randomly draw a marble from the box, replace it, and then randomly draw another marble from the box. (This means that we might observe the same marble twice). What is the probability that both the marbles are white? Write your answer as a decimal accurate to three decimal places.

8. Suppose that 7.3 % of the items produced by a factory are defective. If 5 items are chosen at random, what is the probability that none of the items are defective? Write your answer as a decimal accurate to three decimal places.

9. Suppose that 3.6 % of the items produced by a second factory are defective. If 5 items are chosen at random from the second factory, what is the probability that exactly one of the items is defective? Write your answer as a decimal accurate to three decimal places.

10. Suppose that 2.9 % of the items produced by a third factory are defective. If 5 items are chosen at random from the third factory, what is the probability that exactly two of the items are defective? Write your answer as a decimal accurate to three decimal places.

The mean time between arrivals of customers in a bank is 3 minutes. Write the expression for the exponential distribution for average time between arrivals for any time t (t>=0). If a customer has already arrived in the bank, what is the probability that the next customer will come after 10 minutes? What is the probability that 5 customers will arrive in the one hour interval?

Answer with full steps. Thank you!,

Any half answer or incomplete answer would be send back for refund and reported to Chegg. No direct answers. Well handwritten answers only accepted. I repeat only well hand written answers.

This table uses the data file that contains the scores of the winning teams from the final NBA Championship game. I would like to know if the average winning score is the same for each decade listed in the table. Test the claim that the samples all come from populations with the same mean. Use a significance level of 0.05.

H₀ (null hypothesis):

H₁ (alternative hypothesis):

• Write the F-Table value here:

• What is the P-value:

• Now use your calculator or the formula to find the calculated F value (known as the “test statistic”):

REJECT H₀:   YES or NO

• What is your conclusion? Are the groups the same or is at least one group different? Explain.

Out of the last 48 NBA Championships, 15 of the final games had a winning team score greater than 110 points. Use a 0.01 significance level to test the claim that the true population percentage of NBA Championship final games with a winning score greater than 110 points is more than 30%.

• Label each statement. The one with EQUALITY gets the H₀:

• H₀ (null hypothesis):
• H₁ (alternative hypothesis):

• Write down the value given for the significance level:

• Write the Critical value (the Table value) here:

• Now use your calculator or the formula to tell me the calculated value (known as the “test statistic”):

• What is the P-value:

• REJECT H₀:   YES or NO

• What is your conclusion?

If the winning score of the final game of the 2019 championships is greater than 110 points, do you think that will be an unusual result?

Suppose a flop is said to "have a flush draw possibility" if it contains exactly two cards of the same suit, plus another card of a different suit. For instance, A♥ K♥ 10♠ would have a flush draw possibility, but A♥ K♦ 10♠ would not, and also A♥ K♥ 10♥ would not. What is the probability that the flop has a flush draw possibility?

Discuss the importance of data representation methods for presentation of research findings. Why are certain data visualization techniques more appropriate for certain fields/disciplines?

When survey data indicated that a company needed to improve its​ package-sealing process, an experiment was conducted to determine the factors in the​ bag-sealing equipment that might be affecting the ease of opening the bags without tearing the inner liner of the bag. Data were collected on 19 bags and the plate gap on the​ bag-sealing equipment was used to predict the tear rating of a bag. The results are displayed in the accompanying table and the regression equation is the following. Complete parts​ (a) through​ (c).

ModifyingAbove Upper Y with caret Subscript iYi=0.75380.7538+0.5302Xi​,

with Summation from i equals 1 to n∑i=1nYi=14.6414.64​,

Summation from i equals 1 to n∑i=1nUpper Y Subscript i Superscript 2Y2i=38.6848​,

and Summation from i equals 1 to n∑i=1nXiYi=19.73.

Bag   Plate gap (X)  Tear rating (Y)
1   -0.3   0.03
2   -0.30   0.06
3   1.50   0.41
4   1.50   0.82
5   -0.30   0.36
6   0.00   0.37
7   0.30   0.75
8   0.00   1.98
9   0.00   0.24
10   -1.80   0.17
11   -1.80   0.13
12   2.40   3.72
13   -1.80   0.03
14   0.00   0.52
15   -2.70   0.01
16   -1.80   0.13
17   1.80   0.44
18   2.10   4.06
19   0.30   0.07

a. Determine the coefficient of​ determination, r2​, and interpret its meaning. (Fill in the Blank)

r2 = ___? ​(Round to four decimal places as​ needed.)

What is the meaning of the coefficient of​ determination? (Choose Below)

A. It measures the variability in the actual plate gap from the predicted plate gap.

B. It measures the variability in the actual tear rating from the predicted tear rating.

C. It is the proportion of the variation in the plate gap that is explained by the variability in the tear rating.

D. It is the proportion of the variation in the tear rating that is explained by the variability in the plate gap.

b. Determine the standard error of the estimate.

SYX = ___? ​(Round to four decimal places as​ needed.)

c. How useful do you think this regression model is for predicting the tear rating based on the plate gap in the​ bag-sealing equipment? (Choose Below)

Since the value of r2 is (fairly close to 0, fairly close to 1, fairly close to 0.5, equal to 1, equal to 0) and the value of SYX is (relatively large, relatively small) the regression model is (not very useful, fairly useful) for predicting the tear rating.

An employee at a coffee shop hypothesizes that the harder the espresso grounds are tamped down into the portafilter before​ brewing, the longer the separation time of the​ heart, body, and crema will be. The accompanying data table shows the results of this experiment. The independent variable tamp measures the​distance, in​ inches, between the espresso grounds and the top of the portafilter. The dependent variable time is the number of seconds the​ heart, body, and crema are separated. Complete parts​ (a) through​ (f) below.

Shot   Tamp   Time
1   0.20   15
2   0.55   15
3   0.25   12
4   0.15   13
5   0.20   15
6   0.40   14
7   0.25   15
8   0.50   9
9   0.15   17
10   0.30   13
11   0.20   10
12   0.15   15
13   0.40   18
14   0.45   19
15   0.15   15

Part a) Use the​ least-squares method to develop a single regression equation with Time as the dependent variable and Tamp as the independent variable. (Can you show me the step by step process using PHSTAT on all answers)

part b) Predict the mean separation time for a tamp distance of 0.45 inch.

part c) Plot the residuals versus the time order of experimentation. Are there any noticeable​ patterns?

part d) Compute the​ Durbin-Watson statistic. At the 0.05 level of​ significance, is there evidence of positive autocorrelation among the​ residuals?

Part E) Based on the results of​ (c) and​ (d), is there reason to question the validity of the​ model?

A financial analyst engaged in business valuation obtained financial data on 71 drug companies. Let Y correspond to the​ price-to-book value​ ratio, X1 correspond to the return on​ equity, and X2 correspond to the growth percentage. Use the accompanying data to complete parts a. through e. below.

Price/Book Value Ratio   Return on Equity   Growth%
1.542   12.907   6.508
8.318   11.834   135.645
2.002   12.292   0.105
6.539   25.085   14.264
1.283   8.725   22.836
3.228   38.078   19.078
2.449   25.564   24.663
5.363   19.646   11.692
2.288   22.864   49.979
7.745   69.629   36.793
0.427   3.799   41.008
2.492   9.173   28.801
7.716   29.199   52.003
5.207   17.821   25.109
2.141   29.305   23.926
4.701   31.473   9.484
2.205   14.699   18.464
3.987   11.983   39.184
1.853   14.212   39.512
1.568   14.086   27.082
1.945   14.842   13.154
5.043   20.645   17.266
2.402   14.792   15.935
2.061   5.679   16.697
2.895   11.202   8.386
1.775   16.255   18.286
5.495   24.004   16.761
4.722   14.658   46.442
2.532   6.175   34.053
1.736   19.036   8.595
8.509   39.003   15.028
2.288   15.109   25.053
2.805   19.723   0.299
7.422   18.484   3.213
3.308   20.667   9.601
2.725   34.597   7.055
2.485   15.558   9.485
1.218   10.201   4.647
2.922   23.595   4.057
10.153   91.563   13.267
2.119   1.518   15.803
1.592   9.331   5.703
2.081   19.414   0.071
7.211   5.056   102.681
1.237   42.818   1.588
5.734   90.903   74.072
6.435   19.475   8.923
2.697   27.357   34.435
3.449   13.057   12.105
7.031   24.512   11.599
13.738   81.927   24.506
3.965   1.505   20.266
7.135   3.574   22.226
6.173   31.458   49.851
0.985   5.114   13.289
9.343   47.816   61.191
1.313   13.338   10.761
1.043   35.969   9.143
3.808   28.787   71.102
3.591   17.997   51.744
2.248   13.924   17.045
10.026   132.942   171.276
4.188   21.871   8.614
8.405   11.344   247.699
2.095   17.358   10.863
4.123   19.419   6.425
2.349   8.552   24.613
2.955   18.601   14.207
4.532   21.533   5.816
5.037   49.394   31.464
2.142   19.379   3.863

a. Develop a regression model to predict​ price-to-book-value ratio based on return on equity.

Yi=____ + ____X1i

​(Round to four decimal places as​ needed.)

b. Develop a regression model to predict​ price-to-book-value ratio based on growth.

Yi =____ + ____X2i

​(Round to four decimal places as​ needed.)

c. Develop a regression model to predict​ price-to-book-value ratio based on return on equity and growth.

Yi =____ + ____X1i + ____X2i

​(Round to four decimal places as​ needed.)

d. Compute and interpret the adjusted r2 for each of the three models.

Start with the part​ (a) model.

The adjusted r2 shows that ___% of the variation in ________ is explained by ______ _____ correcting for the number of independent variables in the model.

​(Round to one decimal place as​ needed.)

Compute and interpret the adjusted r2 for the part​ (b) model.

The adjusted r2 shows that ___% of the variation in ____ is explained by ____ ____ correcting for the number of independent variables in the model.

​(Round to one decimal place as​ needed.)

Compute and interpret the adjusted r2 for the part​ (c) model.

The adjusted r2 shows that ____%of the variation in ____ ____ is explained by ____ ____ correcting for the number of independent variables in the model.

​(Round to one decimal place as​ needed.)

e. Which of these three models do you think is the best predictor of​ price-to-book-value ratio?

The model from ___ is the best predictor of​ price-to-book-value ratio because it has the ____ value of ____.

In the description of the statistical models that relate one variable to the other we used terms that suggest a causality relation. One variable was called the "explanatory variable" and the other was called the "response". One may get the impression that the explanatory variable is the cause for the statistical behavior of the response. In negation to this interpretation, some say that all that statistics does is to examine the joint distribution of the variables, but casuality cannot be inferred from the fact that two variables are statistically related.

What do you think? Can statistical reasoning be used in the determination of causality?

As part of your answer in may be useful to consider a specific situation where the determination of casuality is required. Can any of the tools that were discussed in the book be used in a meaningful way to aid in the process of such determination?

A manufacturer of golf equipment wishes to estimate the number of left-handed golfers. How large a sample is needed in order to be 99% confident that the sample proportion will not differ from the true proportion by more than 6%? A previous study indicates that the proportion of left-handed golfers is 8%.

59

136

148

111

Using an article or government report that uses qualitative data, describe what you understand to be the statistical significance of that research. In that same article find the measure of association that was used and explain what information in conveys to you.