A school counselor in a high school would like to try out a new conflict-resolution program to reduce aggressiveness in students. She first surveyed 16 students using a 20-item instrument to measure their levels of aggression (on a scale of 0 to 10, with higher numbers meaning higher aggression levels). One month after the conflict resolution program was implemented, the students were given the same survey. The data are listed in the table below. The school counselor/researcher has set the significance level at α = .05.

4. Calculate the mean from the sample of the difference scores (2 points total: 1 for work, 1 for answer)

5. Estimate the standard deviation of the comparison population (that represents the null hypothesis) (2 points total: 1 for work, 1 for answer)

6. Calculate the standard error (standard deviation of the sampling distribution) (2 points total: 1 for work, 1 for answer)

7. Calculate the t statistic for the sample (2 points total: 1 for work, 1 for answer)

8. Because the hypotheses are directional, a one-tailed test can be performed. Determine the critical t value based on the degrees of freedom and the preset alpha level. (1 point)

1. Using any data sets, run two multiple regression equations. state the dependent and independent variable ( you need to start with at least three and end with at least two) and how you believe they will be related. Run the regression equation until you get to the final model. Then test for the assumptions and interpret the necessary statistics. (use excel Megastat).

Please select from any of the data sets.

Real Estate Data

Baseball2012 Data

Banking Chicago Data

International Data

Variable descriptions

Real Estate Sales data

Variables

X1 = selling price in $000

X2= Number of bedrooms

X3= Size of the home in square feet

X4= Pool (1=yes, 0= no)

X5= Distance from the center of the city in miles

X6= Township

X7= Garage attached (1=yes, 0= no)

X8= Number of bathrooms

105 homes sold

Baseball Data

Variables

X1 = Team

X2= Language (American =1, National =0)

X3= Built (year stadium was built)

X4= Size (stadium capacity)

X5= Salary (total 2012 team salary, $ million)

X6= Wins

X7= Attendance (total for team in millions)

X8= BA (team batting average)

X9= ERA (Team earned run average)

X10= HR (Team home runs)

X11 = Errors (team errors)

X12= SB (team stolen bases)

X13= year

X14= Average player salary ($)

Buena School District Bus Data

Variables

X1 = Bus number

X2= Maintenance cost ($)

X3= (Age)

X4= Miles

X5= Bus type (diesel or gasoline)

X6= Bus Manufacturer (Bluebird, Keiser, Thompson)

X7= Passengers

2. Using any dataset, run an ANOVA test, and interpret the statistically significant Tukey output.

I will be glad if this two questions are answered. My previous question was not answered. Please remember to use MegastatThank you.

5.

Is there sufficient evidence that weekly quizzes have any effect on the midterm scores for groups with computer tutorials, on average? (Consider only groups required to answer the question; there is no need to factor in the other groups; in other words, ignore the groups not included.)

(a) Carry out the appropriate test to answer the question. Paste the corresponding StatCrunch output into your report

Define the null and alternative hypotheses in terms of the population means. What is the value of the test statistic and P-value? What is the null distribution of the test statistic? Based on the P- value, is there sufficient evidence to indicate any effect of weekly quizzes on the midterm scores for groups with computer tutorials?

(a) Two-sample t-test output: 3 points Appropriateness of pooling variances: 2 points Null and alternative hypotheses: 2 points Value of the test statistic: 2 points

the following is the data use stat crunch or excel to answer question 5

Category code score 
C 1 45
C 1 53
C 1 72
C 1 55
C 1 67
C 1 53
C 1 66
C 1 54
C 1 53
C 1 67
C 1 60
C 1 64
C 1 69
C 1 52
C 1 74
C 1 58
C 1 53
C 1 66
C 1 66
C 1 71
H 2 79
H 2 95
H 2 81
H 2 74
H 2 68
H 2 84
H 2 78
H 2 77
H 2 85
H 2 72
H 2 86
H 2 71
H 2 67
H 2 77
H 2 83
H 2 73
H 2 76
H 2 86
H 2 83
H 2 75
Q 3 58
Q 3 66
Q 3 67
Q 3 68
Q 3 64
Q 3 57
Q 3 58
Q 3 57
Q 3 75
Q 3 60
Q 3 63
Q 3 55
Q 3 64
Q 3 51
Q 3 60
Q 3 55
Q 3 61
Q 3 63
Q 3 76
Q 3 64
T 4 51
T 4 57
T 4 73
T 4 67
T 4 63
T 4 77
T 4 67
T 4 81
T 4 70
T 4 82
T 4 61
T 4 58
T 4 80
T 4 68
T 4 76
T 4 60
T 4 69
T 4 68
T 4 86
T 4 64
HT 5 78
HT 5 85
HT 5 86
HT 5 92
HT 5 84
HT 5 78
HT 5 79
HT 5 78
HT 5 95
HT 5 81
HT 5 83
HT 5 76
HT 5 83
HT 5 72
HT 5 81
HT 5 70
HT 5 81
HT 5 90
HT 5 95
HT 5 84
QT 6 55
QT 6 80
QT 6 67
QT 6 89
QT 6 90
QT 6 72
QT 6 75
QT 6 61
QT 6 68
QT 6 56
QT 6 63
QT 6 66
QT 6 64
QT 6 65
QT 6 62
QT 6 70
QT 6 83
QT 6 72
QT 6 65
QT 6 73

5.

Is there sufficient evidence that weekly quizzes have any effect on the midterm scores for groups with computer tutorials, on average? (Consider only groups required to answer the question; there is no need to factor in the other groups; in other words, ignore the groups not included.)

(a) Carry out the appropriate test to answer the question. Paste the corresponding StatCrunch output into your report

Define the null and alternative hypotheses in terms of the population means. What is the value of the test statistic and P-value? What is the null distribution of the test statistic? Based on the P- value, is there sufficient evidence to indicate any effect of weekly quizzes on the midterm scores for groups with computer tutorials?

(a) Two-sample t-test output: 3 points Appropriateness of pooling variances: 2 points Null and alternative hypotheses: 2 points Value of the test statistic: 2 points

the following is the data use stat crunch or excel to answer question 5

Category code score 
C 1 45
C 1 53
C 1 72
C 1 55
C 1 67
C 1 53
C 1 66
C 1 54
C 1 53
C 1 67
C 1 60
C 1 64
C 1 69
C 1 52
C 1 74
C 1 58
C 1 53
C 1 66
C 1 66
C 1 71
H 2 79
H 2 95
H 2 81
H 2 74
H 2 68
H 2 84
H 2 78
H 2 77
H 2 85
H 2 72
H 2 86
H 2 71
H 2 67
H 2 77
H 2 83
H 2 73
H 2 76
H 2 86
H 2 83
H 2 75
Q 3 58
Q 3 66
Q 3 67
Q 3 68
Q 3 64
Q 3 57
Q 3 58
Q 3 57
Q 3 75
Q 3 60
Q 3 63
Q 3 55
Q 3 64
Q 3 51
Q 3 60
Q 3 55
Q 3 61
Q 3 63
Q 3 76
Q 3 64
T 4 51
T 4 57
T 4 73
T 4 67
T 4 63
T 4 77
T 4 67
T 4 81
T 4 70
T 4 82
T 4 61
T 4 58
T 4 80
T 4 68
T 4 76
T 4 60
T 4 69
T 4 68
T 4 86
T 4 64
HT 5 78
HT 5 85
HT 5 86
HT 5 92
HT 5 84
HT 5 78
HT 5 79
HT 5 78
HT 5 95
HT 5 81
HT 5 83
HT 5 76
HT 5 83
HT 5 72
HT 5 81
HT 5 70
HT 5 81
HT 5 90
HT 5 95
HT 5 84
QT 6 55
QT 6 80
QT 6 67
QT 6 89
QT 6 90
QT 6 72
QT 6 75
QT 6 61
QT 6 68
QT 6 56
QT 6 63
QT 6 66
QT 6 64
QT 6 65
QT 6 62
QT 6 70
QT 6 83
QT 6 72
QT 6 65
QT 6 73

1. What are the total abatement costs for the firms and economy to reduce 50% of the emissions with command and control policies?

2. How will cap and trade improve the situation, if each firm will get 2 permits?

3. What is the range of the price per permit so that trade will take place?

Let α ∈ C be a root of x^2 + x + 1 ∈ Q[x]. For γ = 3 + 2α ∈ Q(α), find γ^ −1 as an element of Q(α).

Let a = 3 + 2(2^(1/3)) + 4^(1/3) and b = 1 + 5(4)^(1/3) belong to Q( 2^(1/3)). Calculate a · b and a −1 as elements of Q( 2^(1/3)).

1. Find the appropriate measure of center. Discuss why the chosen measure is most appropriate. Why did you decide against other possible measures of center? 2. Find the appropriate measure of variation. The measure of variation chosen here should match the measure of center chosen in Part 1. 3. Find the graph(s) needed to appropriately describe the data. These may be done by hand and inserted into the Word document. You can also use Excel or a Web Applet to create a Histogram of the chosen data. Graphs can be copied and pasting onto the template. 4. Define the random variable (X) so that your chosen data set represents values of X. 5. Is your chosen random variable discrete or continuous? Explain how you know. 6. Would the Normal or Binomial distribution be a good fit for the underlying sample distribution of X? If one of them is a good fit, state how you would approximate the distribution parameters (Use the mean and standard deviation of the data chosen) 7. If you selected column D, calculate the probability that a flight will depart early or on-time. If you selected column E, calculate the probability that a flight will arrive early or on time using the empirical definition of probability. 8. If you selected column D, calculate the probability that a flight will depart late. If you selected column E, calculate the probability that a flight will arrive late using the empirical definition of probability. 9. For those that selected column D, assume now that the random variable X = Departure Time is exactly normally distributed with mean m= -2.5 and standard deviation s= 23. Compute the probability of a flight arriving late based on this new information. For those that selected column E, assume now that the random variable X = Arrival Time is exactly normally distributed with mean m= -2.5 and standard deviation s= 23. Does this contradict your answer from Part 8? Data: 0 -3 0 -7 8 -1 3 11 -6 -5 -8 -4 -13 -13 -11 -14 -16 -14 -18 -18 -23 -23 2 1 -4 -6 7 -8 -8 -4 -4 -5 -13 -9 -12 -7 -12 1 4 -19 -13 -19 3 12 13 2 0 0 4 -7 8 9 -1 -10 -6 -12 -14 -13 9 -15 -13 -14 20 -16 11 -14 18 -19 -3 -4 0 -3 2 6 6 -6 1 11 -7 -10 -13 9 -13 -18 -17 -11 -20 -18 8 0 -20 -3 1 -1 -4 -6 -5 -8 -10 -9 -6 8 -9 -12 -15 -14 -9 -17 -13 -17 2 -18 -18 -16 1 -4 0 -5 7 -7 -7 -5 0 5 -6 -12 1 6 -10 -15 -18 -16 -17 0 -21 -18 5 1 3 -2 -1 -2 -3 4 3 -11 9 -11 -11 0 -11 17 -10 -11 0 -19 -18 0 8 -23 3 -3 -4 -6 0 2 -1 -9 -9 4 1 -9 -12 0 0 -11 -14 -19 -17 -13 23 8 21 3 4 -2 1 6 7 -9 -3 1 -9 -5 -11 -6 -6 -10 -13 -9 -17 -6 -20 1 -21 -22 -2 0 -4 -3 3 -5 -6 -3 -5 -8 -12 -10 -7 -16 1 -14 -14 -16 -7 13 -17 -16 7 0 1 1 4 1 -8 -5 -9 0 -4 8 -7 -14 7 -8 5 4 8 21 3 11 2 -23 0 4 3 2 0 -1 -7 5 3 8 12 -12 -15 -11 -7 17 -15 -13 -17 -21 4 -19 -24 3 0 4 0 -2 -8 -5 6 5 1 -12 -14 7 8 -16 -11 -17 -20 10 4 -14 -22 -22 -3 -4 2 -4 -2 0 6 -6 2 -9 -3 -10 -13 7 -10 -12 -13 -16 -20 1 -14 -21 -17 3 -1 -1 0 -2 -7 -4 0 11 3 -11 -12 -11 -8 -13 -16 -16 7 2 -21 3 9 0 3 0 -5 -3 -3 -3 -3 -4 9 0 -8 -10 12 5 -16 -16 -13 -13 3 -19 0 -20 2 -3 -2 3 5 -1 -8 -3 -7 -11 -7 -10 12 -12 -8 17 -9 -18 -17 -14 1 -13 -21 -22 -2 -3 3 -3 -2 -7 -5 -10 -8 -6 -13 11 -11 -16 -9 -13 -12 -13 -16 -10 -20 -19 -22 -1 -4 2 4 -3 -8 4 -3 -7 -11 -13 2 -13 -12 -15 3 -17 -10 3 0 -19 -20 -20 0 0 -5 -4 -3 -5 -1 -8 -7 -2 13 11 -10 -12 -15 -14 -17 -18 6 12 6 -19 -20 0 -1 -5 -1 4 6 3 8 0 -11 -8 -14 -13 -11 3 -7 -11 10 -19 -20 -21 0 3 0 -4 0 2 -6 -7 -6 -7 8 -12 -2 -13 -7 9 -15 -14 -14 -17

Solve x" + ? = ???2? , ? (0) = 2, ? ′ (0) = 1
1) manually 2) using Laplace transform. Show step-by-step process

Consider the system: ?[?] − 0.5?[? − 1] − 0.25?[? − 2] = ?[?] + 2?[? − 1] + ?[? − 2]

Assume initial conditions y(-1) = 1, y(-2) = 0 and that the input signal to the system is a discrete-time unit step. Determine the formula for the Z-transform of the solution, Y(z). Subsequently, determine the formula for the solution, y[n], itself.

4. We would prefer to estimate the number of books in a college library without counting them. Data are collected from colleges across Books (in millions)

Using Stepwise regression, show how each of the three factors affects the number of volumes in a college library.