The Downtown Parking Authority of Tampa, Florida, reported the following information for a sample of 229 customers on the number of hours cars are parked and the amount they are charged.

Number of Hours		Frequency		Amount Charged
1		21		$	4
2		38			5
3		50			10
4		45			13
5		18			14
6		16			16
7		5			18
8		36			20
		total 229

a-1. Convert the information on the number of hours parked to a probability distribution. (Round your answers to 3 decimal places.)

a-2. Is this a discrete or a continuous probability distribution? Discrete Continuous

b-1. Find the mean and the standard deviation of the number of hours parked. (Do not round the intermediate calculations. Round your final answers to 3 decimal places.)

b-2. How long is a typical customer parked? (Do not round the intermediate calculations. Round your final answer to 3 decimal places.)

Find the mean and the standard deviation of the amount charged. (Do not round the intermediate calculations. Round your final answers to 3 decimal places.)

Conditions for instruments to be valid include all of the following except: (A) each one of the instrumental variables must be normally distributed. (B) at least one of the instruments must enter the population regression of ?? on the ??s and the ??s. (C) perfect multicollinearity between the predicted endogenous variables and the exogenous variables must be ruled out. (D) each instrument must be uncorrelated with the error term

1. Materials and Introduction:
   1. Each person should have 10 KISSES^® chocolates of the same variety and a 16-ounce plastic cup
   2. Examine one of the KISSES^® chocolates. There are two possible outcomes when a KISSES^® chocolate is tossed - landing completely on the base or not landing completely on the base.
   3. Estimate p, the proportion of the time that a KISSES^® chocolate will land completely on its base when tossed.
   4. We will assume that p is approximately 50% and test the claim that the population proportion of Kisses® chocolates that land completely on the base is less than 50%.
   5. We will assume that p is approximately 35% and test the claim that the population proportion of Kisses® chocolates that land completely on the base is different than 35%.

2. Experiment: The investigation is as follows:

6. Put 10 KISSES^® chocolates into the cup
7. Gently shake the cup twice to help mix up the candies.
8. Tip the cup so the bottom of the rim is approximately 1 – 2 inches from the table and spill the candies.
9. Count the number of candies that land completely on their base.
10. Return the candies to the cup and repeat until you have spilled the candies 5 times.
11. Record your results on the Data Table.

Data Table:

Toss Number	Number of Candies Landing Completely on Base
1
2
3
4
5
Total

3. Questions

We treat the 50 results for each student as 50 independent trials. Actually, each student has ten independent trials of 5 tosses each. We make the assumption that the 10 tosses within a trial are roughly independent to expedite data collection.

1. We will assume that p is approximately 50% for the following two tests.
   1. Test the claim that the population proportion of Kisses® chocolates that land completely on the base is different than 50% at α = 10% level of significance.

State hypotheses and α:

Calculate the evidence – State test used. Clearly state the p-value.

State the complete decision rule then state clearly your decision.

State your conclusion in context to the problem.

2. Test the claim that the population proportion of Kisses® chocolates that land completely on the base is less than 50% at α = 10% level of significance.

State hypotheses and α:

Calculate the evidence – State test used. Clearly state the p-value.

State the complete decision rule then state clearly your decision.

State your conclusion in context to the problem.

2. We will assume that p is approximately 35% for the following two tests.

1. Test the claim that the population proportion of Kisses® chocolates that land completely on the base is different than 35% at α = 5% level of significance.

State hypotheses and α:

Calculate the evidence – State test used. Clearly state the p-value.

State the complete decision rule then state clearly your decision.

State your conclusion in context to the problem.

(I need your Reference URL LINK, please)

( i need Unique answer, don't copy and paste, please) (dont' use handwriting, please).

I need the answer quickly, please :((((((.. pleaaasssee heeelp mmmeeee// i need all answers, UNIQUE ANSWER please

Q1: Define the following terms:(dont' use handwriting, please)

a. correlation coefficient(dont' use handwriting, please)

b. scatter plot(dont' use handwriting, please)

c. bivariate relationship(dont' use handwriting, please)

Q2: Provide an example where the outlier is more important to the research than the other observations?(dont' use handwriting, please)

Q3: Identify when to use Spearman’s rho (dont' use handwriting, please)

( i need Unique answer, don't copy and paste, please) (dont' use handwriting, please)

Find the​ P-value for the indicated hypothesis test with the given standardized test​ statistic, z. Decide whether to reject

Upper H 0H0

for the given level of significance

alphaα.

​Two-tailed test with test statistic

z=- −2.15 0.08

test statistic

z= -2.15 and α=0.08

​P-value=_____

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

2)Find the critical​ value(s) and rejection​ region(s) for the indicated​ t-test, level of significance

α​,and sample size n. Left​-tailed ​test,

α=0.10​,

n=13

The critical​ value(s) is/are

I have done some of this on my own but just cant seem to be able to finish this correctly.

Dual-energy X-ray absorptiometry (DXA) is a technique for measuring bone health. One of the most common measures is total body bone mineral content (TBBMC). A highly skilled operator is required to take the measurements. Recently, a new DXA machine was purchased by a research lab, and two operators were trained to take the measurements. TBBMC for eight subjects was measured by both operators. The units are grams (g). A comparison of the means for the two operators provides a check on the training they received and allows us to determine if one of the operators is producing measurements that are consistently higher than the other. Here are the data.

	Subject
Operator	1	2	3	4	5	6	7	8
1	1.327	1.335	1.077	1.226	0.936	1.004	1.181	1.288
2	1.323	1.322	1.073	1.233	0.934	1.019	1.184	1.304

(a)

Take the difference between the TBBMC recorded for Operator 1 and the TBBMC for Operator 2. (Use Operator 1 minus Operator 2. Round your answers to four decimal places.)

x= -0.0022 (this is correct!)

s= 0.0100 (this is correct!)

Use a significance test to examine the null hypothesis that the two operators have the same mean. Give the test statistic. (Round your answer to three decimal places.)

t = ??? (cant get right answer)

Give the degrees of freedom.

7 (this is correct!)

Give the P-value. (Round your answer to four decimal places.)

??? (cant get right answer)

Give your conclusion. (Use the significance level of 5%.)

a) We can reject H₀ based on this sample

or

b) We cannot reject H₀ based on this sample.     

The sample here is rather small, so we may not have much power to detect differences of interest. Use a 95% confidence interval to provide a range of differences that are compatible with these data. (Round your answers to four decimal places.)

( , ) ??? (cant get right answer)

The eight subjects used for this comparison were not a random sample. In fact, they were friends of the researchers whose ages and weights were similar to the types of people who would be measured with this DXA machine. Comment on the appropriateness of this procedure for selecting a sample, and discuss any consequences regarding the interpretation of the significance-testing and confidence interval results.

a) The subjects from this sample may be representative of future subjects, but the test results and confidence interval are suspect because this is not a random sample.

or

b) The subjects from this sample, test results, and confidence interval are representative of future subjects.   

Part IV: Finding exact probabilities. FOR EACH, DRAW A PICTURE AND USE THE Z-TABLE ON CARMEN.

20. The Z-table always gives you the probability of being between ________ and  the number you are looking up.

21. The number you are looking up should have ______digit(s) before the decimal point and _____ digit(s) after the decimal point.

22. Suppose the Z value is 2.00. Which row and column do you look in to find P(0< Z < 2.00)?

            

23. How do you find P(Z < 2.00)? (Note you have to do this in 2 parts. Hint: What is the probability that Z is less than 0? Use that as one of the parts)

            

24. How do you find P(Z > 2.00)? (Note the table does not have “>” probabilities. If half of the probability is greater than 0, how much of it must be greater than 2? Draw a picture. )

            

25. a. What is P(-1.26  < Z < 0)?  (Note the Z table has no negative values. Use SYMMETRY to do this.)

25.  b.  Find P(Z > -1.26)

25.  c. Find P(Z < -1.26)

26.a   Now find P(-1 < Z < 2). Do this in two parts and sum them together. Use symmetry to get the left part.

26b. Find P(1<Z<2)

Describe a correlation analysis, and provide an example of one. Provide examples of dependent and independent variables, as well.

The average number of sales at a car dealership is 24 with a standard deviation of 5. A week ago, you were promoted to manager. Over this week (seven days), the average number of sales has dipped to 20. Your boss says he is coming by tomorrow to check out how you have been doing. You know that your boss has a rule where he will fire any manager if the average number of sales is statistically lower than 24 with 99% confidence. Are you going to get fired? Complete a one sided hypothesis test.

Z =

p =

Critical Value =

Alpha =

Are you going to get fired?

No /Yes

Participant	Stress Level (X)	Test Score (Y)
1	18	6
2	3	17
3	12	9
4	8	22
5	15	7
6	7	11

What's the slope of this data (round to two decimal places)?

What's the Y intercept (round to two decimal places)?

What's the predicted test score for a stress level of 10 (round to two decimal places)?

What's the error of participant 5's score (round to two decimal places)?

What's the standard error of the estimate?

What is the coefficient of determination?

The following table shows the average distance, to the nearest mile, travelled per week to work by a random sample of 350 commuters.

Miles Travelled Frequency Midpoint Class Boundaries

6 - 11 43

12 - 17 32

18 – 23 80

24 - 29 120

30 - 35 75

(a) Complete the table above.

(b) What is the mean distance travelled per week by these commuters?

(c) Why is the answer for part (b) an estimate of the mean distance travelled?

(d) State one advantage and one disadvantage of using the mean as a measure of central tendency.

(e)What is the modal length of distance travelled by the commuters?

(f) Calculate the variance for the distance travelled per week by the commuters.

Question 1

The average sea surface temperature (in degree Celsius) and the coral growth (in millimetres per year) over 18 years at a particular location are observed. An excerpt of the data is shown in the table below:

Temperature (x)= 29.61 29.82 30.25 … 30.96

Growth (y)= 2.63 2.58 2.49 … 2.26

The output from R Commander appears on the next page

(c) Using the R Commander output, calculate the correlation coefficient between the two variables. [2 marks]

(d) Test the significance of the slope of the linear regression line at the 5% level of significance. State clearly the null and alternative hypotheses, the name of the test or the test statistic, decision rule, test result and conclusion in terms of the original problem. [6 marks]

(e) Write down the linear regression equation for the data. (1MARK)

(f) Interpret the slope of the linear regression equation. [1 mark]

(g) Use the equation in (e), predict the coral growth when the average sea surface temperature is 30 degree Celsius. [1 mark]

(h) Comment on the appropriateness of the prediction in (g). [2 marks]

(i) Write down three assumptions underlying the analysis. [3 marks]

> summary(RegModel.1)

Call: lm(formula = Growth ~ Temperature, data = Q1)

Residuals:

Min 1Q Median 3Q Max

-0.10279 -0.04107 -0.01688 0.04901 0.09864

Coefficients:

Estimate Std. Error t value Pr(>|t|)

(Intercept) 7.81986 1.11135 7.036 2.81e-06 ***

Temperature -0.17860 0.03698 -4.830 0.000185 ***

---

Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 0.06155 on 16 degrees of freedom

Multiple R-squared: 0.5931, Adjusted R-squared: 0.5677

F-statistic: 23.33 on 1 and 16 DF, p-value: 0.0001848

1. Let’s use Excel to simulate rolling two dice and finding the rolled sum.

• Open a new Excel document.

• Click on cell A1, then click on the function icon fx and select Math&Trig, then select RANDBETWEEN.

• In the dialog box, enter 1 for bottom and enter 6 for top.

• After getting the random number in the first cell, click and hold down the mouse button to drag the lower right corner of this first cell, and pull it down the column until 25 cells are highlighted. When you release the mouse button, all 25 random numbers should be present.

• Repeat these four steps for the second column, starting in cell B1.

• Put the rolled sum of two dice in the third column: Highlight the first two cells in the first row and click on AutoSum icon. Once you receive the sum of two values in the third cell, drag the lower right corner of this cell, C1, down to C25. This will copy the formula for all 25 rows. We now have 25 trials of our experiment.

• Once these steps are completed, attach a screenshot of your Excel file to your assignment.

(a) Find the probability that the rolled sum of both dice is 5.

(b) Based on the results of our experiment of 25 trials, obtain the relative frequency approximation to the probability found in (a).

(c) Repeat the simulation for 50 and 100 trials, and calculate the relative frequency approximation to the probability in (a) for each. Which approximation has the closest value to the probability?

(d) Briefly explain how these experiments demonstrate the Law of Large Numbers.

Crop rotation is a common strategy used to improve the yields of certain crops in subsequent growing seasons. An experiment was performed to assess the effects of crop rotation plant type and crop rotation plant density levels on the yield of corn, the primary crop of interest. A field was separated into 12 plots and each of the treatments was randomly applied. After 2 months of growth of the rotated crops, the plots were cleared, and corn seeds were applied evenly to each plot. After 5 months of growth of the corn, the yields were assessed. The data, in kg/m2, are shown below. Determine if crop rotation plant type and density affect the yields of corn in this field. What treatment should the farmers use to maximize the yield?

	Density (k/ha)
Rotation Variety	05 k/ha	10 k/ha	15 k/ha	20 k/ha
Pea	7.8	11.2	18.5	15.4
	9.1	12.7	16.7	14.7
	10.6	13.3	15.4	11.3
Soy	7	9.3	13.8	11.3
	6.7	10.9	14.3	12.7
	8.1	11.8	15.4	14.3
Wheat	6.4	4.9	3.6	2.8
	4.5	7.1	3.9	6.1
	5.9	3.2	5.8	4.6

1. What kind of statistical test will you be performing?
2. Will you need to test for equal variance? If so what are your results and how does that influence the next steps in your analysis?
3. What are your null and alternative hypotheses?
4. Discuss the results of your analysis. Will you accept or reject your null hypothesis? Why? What can you specifically say about the data?

A sleep center hypothesizes that people who sleep only four hours will score lower than people who sleep for eight hours on a cognitive skills test. The center recruited 20 participants and split them into two groups, giving one group 8 hours of sleep and the other only 4 hours. The following morning, the CAT (Cognitive Ability Test) was conducted, with scores ranging from 1-9, 9 being the best score. Use this information to answer questions . CAT Scores Group X: Eight hrs sleep 4 7 9 4 3 3 8 6 3 7 Group Y: Four hrs sleep 7 8 1 4 2 3 5 2 7 4 Conduct the following hypothesis test: - A one-tail T-test for a two-sample difference in means at the 95% confidence level - with Null Hypothesis that the Group X mean CAT score is equal to the Group Y mean CAT score - and with Alternate Hypothesis that the Group X mean CAT score is greater than the Group Y mean CAT score a). Calculate the mean and standard deviation of the scores for each group. (10%)

b)Using the correct degrees of freedom (df = group X size + group Y size ̶ # of groups), the correct number of tails, and at the correct confidence level, determine the critical value of t. (10%)

c). Explain under which scenarios using a pooled variance be inadvisable, then, calculate the pooled variance (formula for S2 is on page 379) for the groups. (10%)

d). Calculate the test statistic, Ttest (formula for t is on page 380). (10%)

e). The sleep center’s statistician tells you that the p-value for the test is 0.1535. Summarize the result of the study. Compare the mean scores in each group. Compare the test statistic to the critical value. Compare the p-value to alpha. Do you find a statistically significant difference between Group X and Group Y on cognitive test performance? Is there a meaningful/practical difference? Explain your decisions and Justify your claims