Select two data values from your raw data – one that is inside of the confidence interval and one that is outside – one must be at the high end of the data and one at the low end – and construct two hypothesis tests, one for each value. One of the tests should be a “less than”, the other should be a “greater than”, depending on the value being tested. Use a 95% level of confidence.

Songs
250
5
800
500
850
430
200
600
0
130
1000
1000
400
1500
20
1500
872
150
115
90
252
2345
200
200
300
200
650
1500
600
500
800
400
930
400
10000
456
200
1200
0
500
30
0
950
180
450
1000
730
10
10
55
260
500
0
1327
0
250
0
35
100
1000
10
35
0
1200
2000
200
1813
15
90
5
100
300
1400
200
22
800
300
1000
15
75
200
700
167
200
183
678
50
350
150
400
2000
2000
900
1
400
300
100
150
300
150
100
1200
1500
200
100
1500
300
300
3000
2000
150
100
200
4000
200
500
1500
500
3600
1567
350
181
400
500
0
250
100
50
300
300
500
2000
60
200
0
100
350
400
1000
40
250
1750
0
0
400
840
200
300
500
0
800
200
400
15
45
170
150
0
2409
350
2100
200
200
25
25
0
200
0
0
1200
450
400
2750
300
300
1869
970
300
2900
1140
40
100
2000
500
1000
0
500
30
0
500
812
0

In an ionic bond, (pick one).

1. The oce manager at a real estate firm makes a pot of co↵ee every morning. The time before it runs out, y, in hours, depends on the number of persons x, working in the oce on that day. Suppose that the pairs of (x, y) values from n = 6 days are given in table below. Number of people, x 1 2 3 3 4 5 Time before co↵ee runs out, y 8 4 5 3 3 1 (a) Calculate the standard deviation of responses, s (follow steps on pages 88 and 89). (b) Calculate the 95% confidence interval for average number of hours when x⇤ = 4 people are working in the oce (follow steps on page 90). (c) Interpret your interval from part (b). 94 (d) Calculate and interpret the 95% prediction interval for the number of hours when x⇤ = 4 people are working in the oce (follow steps on page 91). (e) Interpret your interval from part (d). (f) Calculate r2 (follow steps on page 92). (g) Interpret r2. (h) Compute linear correlation coecient r (follow steps on page 93). (i) Interpret r.

Given are data for two variables, x and y.

(a) Develop an estimated regression equation for these data. (Round your numerical values to two decimal places.)

ŷ =  

(b) Compute the residuals. (Round your answers to two decimal places.)

(d) Compute the standardized residuals. (Round your answers to two decimal places.)

Consider the following data for two variables, x and y.

(a) Compute the standardized residuals for these data. (Round your answers to two decimal places.)

The standardized residual with the largest absolute value is _____ .

Two fair six sided dice are rolled.

(i) What is the probability that the smaller value of the two results is 3 given that the sum of the two results is 8?

(ii) What is the probability that the sum of the two results is at most 5 given that the number 2 appeared at least once?

(iii) What is the probability that the sum of the two results is 7 given that exactly one of the two results is odd?

2 algorithms for Prefix Averages, one that ran in big-Oh n2 time and a
second that ran in big-Oh n time. Code up methods for both algorithms. Show through different
input examples and using the Current Time method call how the polynomial time algorithm runs
slower than the linear time version. Use system.out.println statement to show your results.

please who can help with this question In Java
Thank you

AstraZeneca plc (AZN) stock was trading at $45 in AUG and the following options prices are available: SEPT 40 put - $1.50 SEPT 50 call - $1 Consider a short strangle using AZN by selling one SEPT 40 put and one SEPT 50 call. Answer the following questions. A) What is the maximum profit you would expect from the strangle? B) What are the two break-even prices for AZN on expiration? C) What is the maximum loss you might experience from the strangle? D) The stock price declined to $39 on the expiration. What is the amount of profit or loss from the short strangle?

1. A car dealer believes that average daily sales for four different dealerships in four separate states are equal. A random sample of days results in the following data on daily sales:

Ohio                New York       West Virginia              Pennsylvania

               3                          10                         3                                  20

               2                            0                         4                                  11

               6                            7                         5                                  8

               4                            8                                                             2

               4                            0                                                             14

               7

               2

Use ANOVA to test this claim at the 0.05 level.

2. Use Excel to support your answers to Question 1. Submit your completed Excel spreadsheet.

3. Suppose we have the following data on variable X (independent) and variable Y (dependent):

X         Y

2          70

0          70

4          130

1. By hand, determine the simple regression equation relating Y and X.

2. Calculate the R-Square measure and interpret the result.

3. Calculate the adjusted R-Square.

4. Test to see whether X and Y are significantly related using a test on the population correlation. Test this at the 0.05 level.

5. Test to see whether X and Y are significantly related using a t-test on the slope of X. Test this at the 0.05 level.

6. Test to see whether X and Y are significantly related using an F-test on the slope of X. Test this at the 0.05 level.

4. Suppose we have the following values for a dependent variable, Y, and three independent variables, X1, X2, and X3. The variable X3 is a dummy variable where 1 = male and 2 = female:

X1       X2       X3       Y

0          40        1          30

0          50        0          10

2          20        0          40

2          50        1          50

4          90        0          60

4          60        0          70

4          70        1          80

4          40        1          90

6          40        0          70

6          50        1          90

8          80        1          100

9          90        0          80

9          20        1          150

1. Run the multiple regression in Excel and provide the resulting multiple regression equation.
2. Provide the R-Square measure. Is this a good regression model? Explain. Use a level of significance of 0.05 in any tests you consider.

3. Which variables are important in explaining Y when the level of significance is 0.05? Is the dummy variable important at this level of significance? Discuss what the coefficients mean regarding the effect of each variable on Y.

4. Suppose a female with X1 = 5 and X2 = 80 is selecte What would be her predicted value of Y?

5. What types of problems might exist in this multiple regression?

The Roger’s Company incurred the following costs in the acquisition of a plant asset:What is the cost of the plant asset? Can explain

How does gender socialization influence who runs for office and for whom we vote? How are female politicians treated by the media, compared with male politicians? How has that impacted your own perception of female politicians?