At one point the average price of regular unleaded gasoline was

​$3.543.54

per gallon. Assume that the standard deviation price per gallon is

​$0.080.08

per gallon and use​ Chebyshev's inequality to answer the following.

​(a) What percentage of gasoline stations had prices within

33

standard deviations of the​ mean?

​(b) What percentage of gasoline stations had prices within

2.52.5

standard deviations of the​ mean? What are the gasoline prices that are within

2.52.5

standard deviations of the​ mean?

​(c) What is the minimum percentage of gasoline stations that had prices between

​$3.383.38

and

​$3.703.70​?

The methods of parametric statistics (like t-tests, z-intervals, etc.) can be applied to nominal or ordinal data. Question 1 options: True or False

Question 2 When only ordinal-level data are available, Spearman’s rank correlation can be used to analyze the association between two variables. Question 2 options: True or False

Number of Police Officers (X)    Number of Crimes (Y)

0    10

20    10

   30    40


a. Calculate the correlation coefficient and the covariance

b. Calculate the regression coefficient of the slope.

c. State the regression equation.

d. Interpret the meaning of the intercept and slopes in this equation. Be sure to explain using units.

e. Predict the number of crimes when the number of police officers is 7.

A mill operator is concerned that bags are not being filled to the stated 1000g of grain. 20 bags are randomly weighed and results recorded. There is a sign on the machine that states "grain volumes dispensed follow a normal distribution". a) If a one sample t-test is used, write down the decision rule in terms of a test statistic and calculate the value of the test statistic manually. Use 5% level of significance. b) State the two assumptions of this test and their likely validity.

Bag Weight
1,968.22
2,918.98
3,942.76
4,1024.02
5,988.96
6,1057.26
7,987.28
8,970.06
9,947.76
10,1003.18
11,1005.7
12,1076.16
13,931.36
14,990.06
15,950.64
16,1058.82
17,1036.26
18,928.64
19,898.16
20,978.54

Describe four methods of sampling, and provide examples of each. How could each of these methods be useful in some area of business? Do you think any more method would be more valuable than others? Why or why not?

Directions: Use the Bivatiate Correlation function and the Options submenu to answer each of the questions based on the above scenario.

The superintendent has continued the examination of data by examining the relationship between attendance rate and percent of students eligible for free or reduced priced lunch. The district data used for the analysis are contained below.

School % Free or Reduced Attendance Rate 1 47.0 94.8 2 31.1 96.1 3 58.9 94.9 4 40.9 94.2 5 24.1 95.7 6 50.4 94.8 7 54.7 93.8 8 60.1 92.6 9 49.6 93.6 10 42.9 93.8 11 38.1 92.8

School % Free or Reduced Attendance Rate 12 27.2 99.7 13 58.4 93.4 14 52.4 93.6 15 58.4 94.6 16 64.9 93.0 17 75.5 92.3 18 30.6 95.1 19 79.4 92.8 20 67.3 92.6 21 56.7 95.5 22 74.7 91.8

1. What is the mean percent of students receiving free or reduced lunch? What is the mean attendance rate?

51.97 free or reduced

94.16 attendance

2. What are the standard deviations for the percent of students receiving free or reduced lunch and attendance rate?

15.68 free or reduced

1.71 attendance

3. State an appropriate null hypothesis for this analysis.

4. What is the value of the correlation coefficient?

5. Based on the value of the correlation coefficient, how would you classify the strength of this relationship?

6. Based on the information from the scenario, what is the appropriate value for the degrees of freedom?

7. What is the reported level of significance?

8. Present the results as they might appear in an article. This must include a table and narrative statement that reports and interprets the results of your analysis.

Note: The table must be created using your word processing program. Tables that are copied and pasted from SPSS are not acceptable.

Problem 1

A farm has been experimenting with a special diet for its horses. The feed components for the diet are

a standard feed product, a vitamin-enriched oat product, and a new vitamin and mineral feed additive

(detail below). The minimum daily diet requirements for each horse are 3 units of ingredient A, 6 units

of ingredient B, and 4 units of ingredient C. In addition, to control the weight of the horses, the total

daily feed for a horse should not exceed 6 pounds. The farm would like to determine the minimum-

cost mix that will satisfy the daily diet requirements.

Ingredients [in units] to Produce One Pound of Special Die

Feed Component	Standard	Enriched Oat	Additive
Ingredient A	0.8	0.2	0.0
Ingredient B	1.0	1.5	3.0
Ingredient C	0.1	0.6	2.0
Cost Per Pound	$0.25	$0.50	$3.00

On a separate piece of paper, define the variables and formulate the mathematical model for this problem.

Enter the model into Excel's Solver and solve it. How many pounds of Standard product, Enriched Oat, and Additive should be used in the mix to generate the lowest possible total cost?

Please complete on excel using solver so I can see how to format and what cells to link

Describe a scenario where a researcher could use a One-Way ANOVA to answer a research question. Fully describe the scenario and the variables involved and explain the rationale for your answer. Why is that test appropriate to use? Please do not provide answer with "Goodness of fit" scenario.

Par Inc. is a small manufacturer of golf equipment. It produces two types of golf bags: Standard and Deluxe. Each bag type requires the following operations (and production times) to produce one unit:

	Production Time (hours)		Time Available
Operation	Standard	Deluxe	(hours/month)
Cutting and Dyeing	0.7	1	630
Sewing	0.5	5/6	600
Finishing	1	2/3	708
Inspection	0.1	0.25	135

Time available refers to the production capacity for each of the above operations. For example, 630 total hours a month are available for cutting and dyeing, which will be distributed for the production of the two types of bags.

Every standard bag makes a profit of $10, and every deluxe bag makes a profit of $9.

The problem is to determine the optimal number of standard bags and deluxe bags to produce every month to maximize the profit contribution.

Define the variables, formulate the problem, and SOLVE it in Excel (generate the Answer and Sensitivity reports)

Please use excel and post pictures so I can see how to do this on Excel

Total plasma volume is important in determining the required plasma component in blood replacement therapy for a person undergoing surgery. Plasma volume is influenced by the overall health and physical activity of an individual. Suppose that a random sample of 46 male firefighters are tested and that they have a plasma volume sample mean of x = 37.5 ml/kg (milliliters plasma per kilogram body weight). Assume that σ = 7.30 ml/kg for the distribution of blood plasma.

(a) Find a 99% confidence interval for the population mean blood plasma volume in male firefighters. What is the margin of error? (Round your answers to two decimal places.)

lower limit
upper limit
margin of error

(b) What conditions are necessary for your calculations? (Select all that apply.)

σ is knownn is largethe distribution of weights is uniformthe distribution of weights is normalσ is unknown

(c) Interpret your results in the context of this problem.

99% of the intervals created using this method will contain the true average blood plasma volume in male firefighters.The probability that this interval contains the true average blood plasma volume in male firefighters is 0.01.    The probability that this interval contains the true average blood plasma volume in male firefighters is 0.99.1% of the intervals created using this method will contain the true average blood plasma volume in male firefighters.

(d) Find the sample size necessary for a 99% confidence level with maximal margin of error E = 2.10 for the mean plasma volume in male firefighters. (Round up to the nearest whole number.)
male firefighters

******Show work, no Exel/Spss please!!!!******

1. To answer this question, refer to the following hypothetical data collected using replicated measures design.

Subject	1	2	3	4	5	6	7	8	9	10
Pre	50	49	37	16	80	42	40	58	31	21
Post	56	50	30	25	90	44	60	71	32	22

a) In a two-tailed test of H 0 using α=0.05, what is p(obtained) for the results shown? *Hint: "two-tailed" means the same thing as nondirectional. ANSWER = 0.0216

b) What would you conclude regarding H0 using a = 0.05 2-tail? ANSWER = Reject H0

2. Conduct a one-way ANOVA on the following data.

Group 1	4	9	10
Group 2	11	11	10
Group 3	1	6	4

What is your conclusion (use an alpha)? ANSWER = Reject H0

3. What is the value of r for the following relationship between height and weight? ANSWER = 0.87

Height: 60, 64, 65, 68 Mean=62.25

Weight: 103, 122, 137, 132 Mean=123.5

4. Given the following data, what is the value of F crit for the column effect (variable b) *Hint: don't forget to evaluate a numerator (for variable B) and denominator df (within): ANSWER= 3.40

	Variable B
Variable A	1	2	3
1	5	4	4
	2	6	9
	1	3	7
	4	1	5
	2	3	4
2	6	6	5
	2	7	7
	3	4	5
	3	3	4
	2	3	8

5. Given the following data, what is the value of the SS total? ANSWER = 121.8667

	Variable B
Variable A	1	2	3
1	5	4	4
	2	6	9
	1	3	7
	4	1	5
	2	3	4
2	6	6	5
	2	7	7
	3	4	5
	3	3	4
	2	3	8

6. What is the value of the MS rows in the following ANOVA table? ANSWER = 225.25

Source	SS	DF	MS	F obt
Rows	450.5	2	225.25	0.11
Columns	116.4	1	116.40
Interaction	2.3	2	1.15
Within-Cells	829.6		10.85
Total		29

1. You know the true properties of the data so you can answer the two following questions: (and you do not need to know the Y values to answer)

Expected value= 0 Variance= 10

a. What is the true variance of beta hat 1?

b. What is the true variance of beta hat 2?

Observation Number	X
1	5
2	8
3	10
4	4
5	5
6	12
7	2
8	6
9	3
10	6

Suppose we suspect a coin is not fair — we suspect that it has larger chance of getting tails than heads, so we want to conduct a hypothesis testing to investigate this question.

a: Let p be the chance of getting heads, write down the alternative hypothesis Ha and the null hypothesis H0 in terms of p.

b: In order to investigate this question, we flip the coin 100 times and record the observation. Suppose we use T = the number of heads as our test statistic, consider two potential rejection regions, 1. T ≥ 80 2. T ≤ 20 Which rejection region will help us reject H0 in favor of Ha?

c: Consider different cases where we observe T = 10, T = 90 and T = 50, what will be our corresponding conclusions given the choice of RR we made in part b?

1. in the statistical analysis section, the authors write: “Post hoc power calculations of our sample size with 107 per group was 95% (5% significance) to detect an increase readmission rate as found in the study;…..”.

Comment. [2 marks]

It's an open question and I have no idea what to answer, so u have any idea please feel free to answer!

The shares of the U.S. automobile market held in 1990 by General Motors, Japanese manufacturers, Ford, Chrysler, and other manufacturers were, respectively, 34%, 32%, 19%, 9%, and 6%. Suppose that a new survey of 1,000 new-car buyers shows the following purchase frequencies: GM Japanese Ford Chrysler Other 397 259 231 80 33 (a) Show that it is appropriate to carry out a chi-square test using these data. Each expected value is ≥ (b) Test to determine whether the current market shares differ from those of 1990. Use α = .05. (Round your answer to 3 decimal places.) x2 H0 . Conclude current market shares from those of 1990.