The data in the table is the number of absences for 77 students and their corresponding grade.

Step 1 of 5 : Calculate the sum of squared errors (SSE). Use the values b0=5.4276b0=5.4276 and b1=−0.4413b1=−0.4413 for the calculations. Round your answer to three decimal places.

step2: Calculate the estimated variance of errors, se2. Round your answer to three decimal places.

step3 : Calculate the estimated variance of slope, sb12. Round your answer to three decimal places.

step 4: Construct the 90%confidence interval for the slope. Round your answers to three decimal places.

step 5: Construct the 80% confidence interval for the slope. Round your answers to three decimal places.

Business Scores on the Graduate Management Association Test (GMAT) are approximately normally distributed. The mean score for 2013–2015 was 552 with a standard deviation of 121. For the following exercises, find the probability that a GMAT test taker selected at ran dom earns a score in the given range, using the normal distribution as a model. (Data from: www.gmac.com.)

31. Between 540 and 700

32. Between 300 and 540

34. Less than 400

35. Greater than 750

36. Between 600 and 700

Using the data set below:

1. Draw a Histogram
2. Draw a polygon
3. After listening to YouTube “histogram and polygon,” explain how histogram is different and similar to polygon.

1. A researcher is interested to learn if there is a linear relationship between the hours in a week spent exercising and a person’s life satisfaction. The researchers collected the following data from a random sample, which included the number of hours spent exercising in a week and a ranking of life satisfaction from 1 to 10 ( 1 being the lowest and 10 the highest). Participant Hours of Exercise Life Satisfaction 1 3 1 2 14 2 3 14 4 4 14 4 5 3 10 6 5 5 7 10 3 8 11 4 9 8 8 10 7 4 11 6 9 12 11 5 13 6 4 14 11 10 15 8 4 16 15 7 17 8 4 18 8 5 19 10 4 20 5 4

a. Find the mean hours of exercise per week by the participants.

b. Find the variance and standard deviation of the hours of exercise per week by the participants.

c. Run a bivariate correlation to determine if there is a linear relationship between the hours of exercise per week and the life satisfaction. Report the results of the test statistic using correct APA formatting. d. Run a linear regression on the data. Report the results, using correct APA formatting. Identify the amount of variation in the life satisfaction ranking that is due to the relationship between the hours of exercise per week and the life satisfaction (Hint: the R2 value) e. Report a model of the linear relationship between the two variables using the regression line formula.

i want all part in R code

(1) The purity of oxygen produced by a fractionation process and the percentage of hydrocarbons in the main condensor of the processing unit, (2) The weight and systolic blood pressure of a group of males in the age group 25-30, (3) The number of pounds of steam used per month at a plant and the average monthly ambient temperature. Answer the following questions for each data sets. (i) Draw the scatter plot. (ii) Fit a simple linear regression model and draw the fitted regression line in the scatter plot. (iii) Report the fitted values and corresponding residuals. (iv) Calculate the coefficient of determination and comment. (v) Test whether intercept of the above model is zero. (vi) Test whether slope of the above model is zero. (vii) Construct analysis-of-variance table and comment. (viii) Find 95% confidence interval on the intercept. (ix) Find 95% confidence interval on the slope. (x) Find 95% confidence interval on the mean purity, symbolic blood pressure and steam usage when the hydrocarbon percentage, weight of a male in the age group 25-30 and average monthly ambient temperature are 1, 160 and 58 unit respectively. (xi) Find 95% prediction interval on the purity, symbolic blood pressure and steam usage when the hydrocarbon percentage, weight of a male in the age group 25-30 and average monthly ambient temperature are 1, 160 and 58 unit respectively. (xii) Compute and plot 95% confidence and prediction bands around the fitted line. (xiii) Which is the wider band and why?

What is a project timeline? assume give a time line for a project you would work on that has at least three tasks

68% of all Americans are home owners. If 36 Americans are randomly selected, find the probability that

a. Exactly 23 of them are are home owners.
b. At most 23 of them are are home owners.
c. At least 24 of them are home owners.
d. Between 21 and 25 (including 21 and 25) of them are home owners.  

Scores on a certain intelligence test for children between ages 13 and 15 years are approximately normally distributed with μ=101 and σ=15.

(a) What proportion of children aged 13 to 15 years old have scores on this test above 91 ? (NOTE: Please enter your answer in decimal form. For example, 45.23% should be entered as 0.4523.) Answer:

(b) Enter the score which marks the lowest 20 percent of the distribution. Answer:

(c) Enter the score which marks the highest 5 percent of the distribution. Answer:

1. The Crown Bottling Company has installed a new bottling process that will fill 12- ounce bottles of Cola. Both overfilling and underfilling of bottles is undesirable. The company wishes to see whether the mean bottle fill, µ, is approximately the target of 12 ounces. The standard deviation of the process is such that σ=0.41. The company samples 32 bottles. Use a hypothesis test, at a 5% level of significance, and the sample mean to determine whether the filler should be adjusted. The sample mean: 12.17

a) What is the null hypothesis and what is the alternative hypothesis?

b) What is the rejection region? Show it in a picture and explain.

c) What test statistic should you use? What is the value of your test statistic?

d) What is your conclusion with respect to the null hypothesis?

2. Now suppose the company is trying to cut costs and wants to limit overfilling of bottles by more than 0.10 ounces. Use a one-tailed hypothesis test to determine whether the mean is more than 12.10 ounces. (Hint: follow all the steps outlined above)

Step by step and well explained, please. Thanks in advance

For all of these questions don't use the p value method instead use the "5 steps of hypothesis testing." Or I will get all of these wrong and I really need the help!!

4) 18.3% of incoming freshmen indicate they will major in business or a related field. A random sample of 350 incoming college freshmen were asked their preference and 65 replied they were considering business as a major. Estimate the true proportion of freshman business majors with 98% confidence.

5) The average length of a prison term in the US for white collar crime is 34.9 months. A random sample of 45 prison terms indicated a mean stay of 35.8 months with a standard deviation for the population of 8.9 months.. At α (alpha) = 0.04, is there sufficient evidence to conclude the average stay differs from 34.9 months?

6) The average 1-ounce chocolate chip cookie contains 110 calories. A random sample of 8 different brands of 1-ounce chocolate chip cookies resulted in the following calories amounts. At the α (alpha) = 0.01 level, is there sufficient evidence that the average calorie content is greater than 110 calories? 100 125 150 160 120 125 145 100

Multiple choice

1. Suppose Ho: yogurt containers average 8 ounces and Ha: yogurt containers average >8 ounces. you made a type 2 error. What is the impact of this? A.not enough information to tell.B.yogurt company is told they are overfilling containers but they really were not. C.yogurt company is overfilling containers but you didn't catch it.

2. Suppose Ho: average bank deposit = $100 and Ha: average bank deposit not equal to $100. Your results tell you there's not enough evidence to reject Ho. What type of error could you be making? A. Type 1 error B. You could be making both Type 1 and Type 2 errors C. Not enough information to tell D. Type 2 error

3. Suppose you are doing a hypothesis test and your p-value is .12. What do you conclude? A. reject Ho B. two choices are correct here C. accept Ho O D. fail to reject Ho

4. Which of the following is true? A. p-values stay the same with new samples and so do significance levels O B. p-values change with new samples but significance levels stay the same C. p-values change with new samples and so do significance levels O D. p-values stay the same with new samples but significance levels change

5. Suppose we used StatCrunch to find the exact test statistic for a two-tailed (not equal to) hypothesis test for the mean, and it turned out to be 1.33. The population standard deviation is known. What is the p-value? A. 0.4082 B. None of the other choices is correct C. 0.0918 D. 0.1836

Consider the set of ordered pairs shown below. Assuming that the regression equation is y with caret=5.322-0.029x and the SSE=18.794​, construct a​ 95% prediction interval for x=6.    

x 4 6 3 3 5   

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

 y 6 7 4 7 2

Click the icon to view a portion of the​ student's t-distribution table. Calculate the upper and lower limits of the prediction interval.

UPL=

LPL=

An article in Electronic Packaging and Production (2002, vol. 42) considered the effect of X-ray inspection of integrated circuits. The radiation dose (rads) were studied as a function of current (in milliamps) and exposure (in minutes).The data arein excel file uploaded to Moodle. Name of the file is “Assignment 4 Data”. Use a software (preferable MINITAB) to answer the following questions.

Part 1. Perform simple linear regression analysis with the variables, radiation dose and exposure time to answer the following questions. (Include the output in your pdf file.)

1. a) Determine response variable and find the fitted line. (Estimated regression line)

2. b) Predict the radiation dose when exposure time is 15 seconds.

3. c) Estimate the standard deviation of radiation dose.

4. d) What percentage of variability in radiation dose can be explained by the

   exposure time?

5. e) Obtain 95% CI for the true slope of regression line.

*****Can you solve the problem above using Minitab and show the steps please?

Probabilities and areas under a curve

Discuss why probabilities for the normal distribution and other continuous distributions are the same as areas under the curve for a given interval.

Consider the following set of dependent and independent variables. Use this data to complete parts a and b below.

Construct a​ 95% confidence interval for the regression coefficient for x1

y   x1   x2
10   2   15
14   7   8
15   5   12
17   9   12
22   6   0
23   12   9
29   13   5
33   20   2

a. The​ 95% confidence interval for the true population coefficient B1 is _____ to _____. (Round to three decimal places as​ needed.)

b. Construct a​ 95% confidence interval for the regression coefficient for x2.

The​ 95% confidence interval for the true population coefficient β2 is ______ to _____. ​(Round to three decimal places as​ needed.)