## U1IP_Stats

Course: Statistics

Complete the following problems in the text:

• Problem 1.2
• Problem 1.26
• Problem 1.30
• Problem 1.48
• Problem 1.50

U1IP_Stats
1.2 Do you work hard for your money? Java professionals think they do, reporting long working hours at their jobs. Java developers from around the world were surveyed about the number of hours they work weekly. Listed here are the average number of hours worked weekly in various regions of the United States and the world. Region Hours Worked U.S 48 Northeast 47 Mid-Atlantic 49 South 47 Midwest 47 Central Mt 51 California 50 Pacific NW 47 Canada 43 Europe 48 Asia 47 South America and Africa 49 SOURCE: Jupitermedia Corporation a.How many hours do you work per week (or anticipate working after you graduate)? b.What happened to the 40-hour workweek? Does it appear to exist for the Java professional? c.Does the information in this chart make a career of being a Java professional seem attractive? 1.26 Suppose a 12-year-old asked you to explain the difference between a sample and a population. a.What information should your answer include? b.What reasons would you give him or her for why one would take a sample instead of surveying every member of the population? 1.30 A coin-operated coffee vending machine dispenses, on the average, 6 oz of coffee per cup. Can this statement be true of a vending machine that occasionally dispenses only enough to fill the cup half full (say, 4 oz)? Explain. 1.48 The election board’s voter registration list is not a census of the adult population. Explain why. 1.50 How have computers increased the usefulness of statistics to professionals such as researchers, government workers who analyze data, statistical consultants, and others?

## EX 10

Complete Exercise 10 in Statistics for Nursing Research: A Workbook for Evidence-Based Practice, and submit as directed by the instructor.

EX 10

## In preparation for writing your report to senior management next week, conduct the following descriptive statistics analyses with Excel. Answer the questions below in your Excel sheet or in a separate

In preparation for writing your report to senior management next week, conduct the following descriptive statistics analyses with Excel. Answer the questions below in your Excel sheet or in a separate Word document:

• Insert a new column in the database that corresponds to “Annual Sales.” Annual Sales is the result of multiplying a restaurant’s “SqFt.” by “Sales/SqFt.”
• Calculate the mean, standard deviation, skew, 5-number summary, and interquartile range (IQR) for each of the variables.
• Create a box-plot for the “Annual Sales” variable. Does it look symmetric? Would you prefer the IQR instead of the standard deviation to describe this variable’s dispersion? Why?
• Create a histogram for the “Sales/SqFt” variable. Is the distribution symmetric? If not, what is the skew? Are there any outliers? If so, which one(s)? What is the “SqFt” area of the outlier(s)? Is the outlier(s) smaller or larger than the average restaurant in the database? What can you conclude from this observation?
• What measure of central tendency is more appropriate to describe “Sales/SqFt”? Why?

## Statistics study analysis

I.               Use the Sleep Patterns and Energy Drinks study below, and answer the following questions:

A. What sampling technique was used for the study?

B. What was the level of measurement for each type of data collected in the study?

C. What descriptive statistics were used in the study? Name them all.

D.  What hypothesis was tested in the study?

E.  What type of test was run on the data?

F.  What was the significance level for the hypothesis test?

G.  What conclusions did the researcher draw?

H.  Were the conclusions appropriate for the study?

I. What were the limitations of the study?

Sleep Patterns and Energy Drinks

A researcher decides to study the relationship between the consumption of energy drinks and the amount of sleep that college students report.  He does a survey of students at a local college where he has used a random numbering scheme to select 100 students to send the survey to. Initially his survey questions included questions about class in school—Freshman—Senior, age, marital status, class load, hours of sleep on average during the week and on the weekend, number of energy drinks consumed on week days and on the weekends.  When he refined his questions, he decided to include questions about consumption of other forms of caffeine as well—coffee, teas, and soda. He believes that students who consume energy drinks are getting less sleep than those who do not, but he decides that he needs the other caffeine data as well and decides to split his group up into three groups once he collects the data—no caffeine use, caffeine use but no energy drinks, and energy drink users (whether or not they use caffeine in other forms).

He gets 72 surveys returned and divides them up into groups according to caffeine use as indicated above with the following results:

No caffeine group n = 15, sleep per night mean = 7.23 hours, sd = 1.72 hours

Caffeine, no energy group n = 27, sleep per night mean = 7.17 hours, sd = 1.58

Energy drink group n = 30, sleep per nigh mean = 6.42, sd = 1.87

He runs a statistical comparison between the groups and finds F= 7.923, p = .032 .

He concludes that there is a significant difference between the groups at p =05 and decides to do further tests to see where the difference lies.

## (STATISTICS)Expansion Strategy and Establishing a Re-Order Point. Write a 1,050-word report based on the Bell Computer Company Forecasts data set and Case Study Scenarios. DUE 8PM EASTERN MONDAY 5/15

This assignment has two cases. The first case is on expansion strategy. Managers constantly have to make decisions under uncertainty. This assignment gives students an opportunity to use the mean and standard deviation of probability distributions to make a decision on expansion strategy. The second case is on determining at which point a manager should re-order a printer so he or she doesn’t run out-of-stock. The second case uses normal distribution. The first case demonstrates application of statistics in finance and the second case demonstrates application of statistics in operations management.

Assignment Steps

Resources:

Microsoft Excel®, Bell Computer Company Forecasts data set, Case Study Scenarios

Write

a 1,050-word report based on the Bell Computer Company Forecasts data set and Case Study Scenarios.

Include

Case 1: Bell Computer Company

• Compute the expected value for the profit associated with the two expansion alternatives. Which decision is preferred for the objective of maximizing the expected profit?
• Compute the variation for the profit associated with the two expansion alternatives. Which decision is preferred for the objective of minimizing the risk or uncertainty?

Case 2: Kyle Bits and Bytes

• What should be the re-order point? How many HP laser printers should he have in stock when he re-orders from the manufacturer?

Format

your assignment consistent with APA format.

Content

Met

Partially Met

Not Met

Write a 1,050-word report based on the Bell Computer Company Forecasts data set and Case Study Scenarios.

Case 1: Bell Computer Company

·       Compute the expected value for the profit associated with the two expansion alternatives. Which decision is preferred for the objective of maximizing the expected profit?

Compute the variation for the profit associated with the two expansion alternatives. Which decision is preferred for the objective of minimizing the risk or uncertainty?

Case 2: Kyle Bits and Bytes

·       What should be the re-order point? How many HP laser printers should he have in stock when he re-orders from the manufacturer?

3

#/3

Writing Guidelines

Met

Partially Met

Not Met

The paper—including tables and graphs, headings, title page, and reference page—is consistent with APA formatting guidelines and meets course-level requirements.

Intellectual property is recognized with in-text citations and a reference page.

Paragraph and sentence transitions are present, logical, and maintain the flow throughout the paper.

Sentences are complete, clear, and concise.

Rules of grammar and usage are followed including spelling and punctuation.

Total Available

Total Earned

2

#/2

Assignment Total

#

5

#/5

(STATISTICS)Expansion Strategy and Establishing a Re-Order Point. Write a 1,050-word report based on the Bell Computer Company Forecasts data set and Case Study Scenarios. DUE 8PM EASTERN MONDAY 5/15
Case Study – Week 3 Individual Assignment QNT/561 Version 9 Case Study – Bell Computer Company The Bell Computer Company is considering a plant expansion enabling the company to begin production of a new computer product. You have obtained your MBA from the University of Phoenix and, as a vice-president, you must determine whether to make the expansion a medium- or large- scale project. The demand for the new product involves an uncertainty, which for planning purposes may be low demand, medium demand, or high demand. The probability estimates for the demands are 0.20, 0.50, and 0.30, respectively. Case Study – Kyle Bits and Bytes Kyle Bits and Bytes, a retailer of computing products sells a variety of computer-related products. One of Kyle’s most popular products is an HP laser printer. The average weekly demand is 200 units. Lead time (lead time is defined as the amount of time between when the order is placed and when it is delivered) for a new order from the manufacturer to arrive is one week. If the demand for printers were constant, the retailer would re-order when there were exactly 200 printers in inventory. However, Kyle learned demand is a random variable in his Operations Management class. An analysis of previous weeks reveals the weekly demand standard deviation is 30. Kyle knows if a customer wants to buy an HP laser printer but he has none available, he will lose that sale, plus possibly additional sales. He wants the probability of running short (stock-out) in any week to be no more than 6%. Copyright © 2017 by University of Phoenix. All rights reserved.

## The Logic of MANOVA

The Logic of MANOVA

Resources

• Multivariate Statistics Discussion Scoring Guide.

In this discussion, the logic of MANOVA will be discussed. Complete instructions are attached. Please cite all references.

The Logic of MANOVA
DIRECTIONS: Discuss the bulleted aspects below, cite references The Logic of MANOVA . Discuss the logic of the MANOVA. Why would a researcher use MANOVA instead of running several separate analyses of variance? Mention specific advantages and disadvantages in doing so.

## Assignment: Analyzing SPSS (PASW) Software: Part 2

Assignment: Analyzing SPSS (PASW) Software: Part 2

For this assignment you use SPSS (PASW) software and learn to properly munipulate data according the APA requirements. This is an important skill and will be a major factor in future assignments in this course, your doctoral studies and dissertation. It is strongly encouraged that you review Chapter 5 of the APA Publication Manual to understand table and figure requirements before starting.

Follow the directions for using SPSS (PASW) in this assignment:

You will then write a 5-6 page paper in which you present your table and an analysis of your findings. Keep in mind that you cannot draw conclusions without further testing. Instead identify notable trends, patterns, relationships, associations, etc. Your paper must meet the following requirements.

Assignment: Analyzing SPSS (PASW) Software: Part 2
Week 2 Application Directions Open the Main Dataset file located in Resources and use the File > Open > Data function to import the data into PASW, making sure to import only the range from A1 to J52 on the Excel worksheet. Add an ordinal variable to the PASW worksheet titled EXPERIENCE, with three classifications Low (0 to 5 years), Medium (6 to 10 years) and High (11+ years). Enter Low for supervisors BOS-1, BOS-4, BOS-7, BOS-10, BOS-13, PHO-1, PHO-4, PHO- 7, PHO-10, PHO-13, PHO-16, PHO-19, SEA-1, SEA-4, SEA-7, SEA-10, SEA-13, and SEA- 16. Use Medium for supervisors BOS-2, BOS-5, BOS-8, BOS-11, BOS-14, PHO-2, PHO-5, PHO-8, PHO-11, PHO-14, PHO-17, SEA-2, SEA-5, SEA-8, SEA-11, SEA-14, and SEA-17. Use High for BOS-3, BOS-6, BOS-9, BOS-12, BOS-15, PHO-3, PHO-6, PHO-9, PHO-12, PHO-15, PHO-18, SEA-3, SEA-6, SEA-9, SEA-12, and SEA-15. Ensure all variables are designated as numeric, except for Site, Supervisor, SupervisorGender, Experience and Operations, which are string variables. Save the file to your computer under a unique name, ensuring that Site (width = 7; Nominal), Supervisor (width = 6; Nominal), Experience (width = 8; Ordinal), NumEmps (width = 11; Scale), HoursWorked (width = 11; Scale), SupervisorGender (width =6; Nominal), PerSafeBeh (width = 11; Scale), InjuryRate (width = 13; Scale), Safety Climate (width = 11; Scale), Risk (width = 11; Nominal) and Operations (width = 50; Nominal). Al variables are String, except for the Scale variables which are numeric. Open the file and ensure all data are included on the PASW file. Eliminate extraneous variables, usually in the columns led or headed by terms like VAR00011, VAR00012, etc.

## Statistics Assignment

Using the information supplied in the attachement, determine the expected amount of time it will take George to travel from Washington, DC to his sister’s house, employing both the I-95 and alternate route. SHOW YOUR WORK, DEMONSRATING HOW YOU ARRIVED AT THE ANSWERS YOU PROVIDE

Statistics Assignment
George’s Thanksgiving Trip George is invited by his sister, Dorothy, to attend a family reunion during the Thanksgiving weekend. Dorothy lives in Denver, NY, about 90 miles northeast of New York City. George lives in Washington, DC, about 215 miles south of New York City. George decides to visit Dorothy and to travel to her place by car. The only problem is that road traffic during the Thanksgiving holidays is terrible along the East Coast of the United States. George would normally travel to Dorothy’s house by taking Interstate Highway 95. This is the major link connecting Washington and New York City. However, during Thanksgiving, the traffic on I-95 is usually bad, leading to major delays. George decides to explore an alternate route to traveling to Dorothy’s. This route would be a few miles longer. Also, he would encounter a 60 mile segment of road in a rural area, and he would have to travel slowly on this segment. The good feature about the alternate route is that it is unlikely to suffer from Thanksgiving traffic. A map showing the two routes to Dorothy’s house is offered in Figure 1. Based on his experience in traveling along I-95 during Thanksgiving holidays, George has developed a good sense of the likelihood of delays that he can encounter on the journey. Table 1 shows the probability distributions he has created for all the segments of his trip to Dorothy for both the I-95 route and the alternate route. Assignment Using the information supplied in Figure 1 and Table 1, determine the expected amount of time it will take George to travel from Washington, DC to his sister’s house, employing both the I-95 and alternate route. SHOW YOUR WORK, DEMONSRATING HOW YOU ARRIVED AT THE ANSWERS YOU PROVIDE. Probability Distributions for Travel Times on Journey Regular Route (East Route) Probability achieving schedule Probability 10% longer than schedule Probability 20% longer than schedule Probability 30% longer than schedule Probability 40% longer than schedule Segment Washington-Baltimore 0.7 0.3 0.0 0.0 0.0 Baltimore-New York City 0.0 0.1 0.2 0.5 0.2 New York City-Kingston 0.1 0.2 0.3 0.3 0.1 Kingston-Sister’s Home 0.8 0.2 0.0 0.0 0.0 Alternate Route (West Route) Probability of achieving schedule Probability 10% longer than schedule Probability 20% longer than schedule Probability 30% longer than schedule Probability 40% longer than schedule Segment Washington-Baltimore 0.7 0.3 0.0 0.0 0.0 Baltimore-Binghamton 0.9 0.1 0.0 0.0 0.0 Binghamton-E Branch 0.9 0.1 0.0 0.0 0.0 E Branch-Sister’s Home 0.8 0.2 0.0 0.0 0.0 3

## numerical analysis

Using the attached information/data: Write a 2- to 3-page analysis of your multiple regression using dummy variables results for each research question. In your analysis, display the data for the output. Based on your results, provide an explanation of what the implications of social change might be.

numerical analysis
Research Question: Rs occupational prestige score is the dependent variable. My independent variables are highest year of school completed, respondent age, and a dummy variable of American citizenship categorized as 1 (if yes) and 2 (if no) and 0 (if otherwise). Are the highest year of school completed, respondent age and dummy variable significant for predicting Rs occupational prestige score? Also what is the effect on Rs occupational prestige score with a unit increase in highest year of school completed, respondent age, and American citizenship? Coefficients significance and interpretation With p-value less than alpha (0.05), highest year of school completed and coefficient of respondent age. But with p-value greater than alpha (0.05) yes and no are not significant. With one unit increase in highest year of school completed, there is 2.324 units increase in Rs occupational prestige score. With one unit increase in respondent age, there is 0.112 units increase in Rs occupational prestige score. Rs occupational prestige score is .335 units less on an average for American citizens as compared to that of others. And Rs occupational prestige score is 2.487 units more on an average for American citizens as compared to that of others Assumptions From the table of correlations I observe that there is no correlation between independent variables. Therefore there is no problem of multicollinearity and the assumption of independence of variables is satisfied. All correlations lie in the interval [-.3, 3] implying no weak linear relationship or no correlation. From the graph of residual I observe that residuals are normally distributed. This implies that the assumption normality of residuals is also satisfied. From the graph of regression standardized residual the constant variance is observed. This implies that assumption of homogeneity of variance is satisfied. Thus all assumptions of regression analysis are satisfied. Output Correlations Rs occupational prestige score (2010) AGE OF RESPONDENT HIGHEST YEAR OF SCHOOL COMPLETED yes no Rs occupational prestige score (2010) Pearson Correlation 1 .126** .514** .028 -.077** Sig. (2-tailed) .000 .000 .165 .000 2427 2421 2426 2427 2427 AGE OF RESPONDENT Pearson Correlation .126** 1 -.014 .036 -.083** Sig. (2-tailed) .000 .479 .068 .000 2421 2529 2528 2529 2529 HIGHEST YEAR OF SCHOOL COMPLETED Pearson Correlation .514** -.014 1 .088** -.201** Sig. (2-tailed) .000 .479 .000 .000 2426 2528 2537 2537 2537 yes Pearson Correlation .028 .036 .088** 1 -.172** Sig. (2-tailed) .165 .068 .000 .000 2427 2529 2537 5054 5054 no Pearson Correlation -.077** -.083** -.201** -.172** 1 Sig. (2-tailed) .000 .000 .000 .000 2427 2529 2537 5054 5054 **. Correlation is significant at the 0.01 level (2-tailed). Variables Entered/Removeda Model Variables Entered Variables Removed Method no, AGE OF RESPONDENT, yes, HIGHEST YEAR OF SCHOOL COMPLETEDb . Enter a. Dependent Variable: Rs occupational prestige score (2010) b. All requested variables entered. Model Summaryb Model R R Square Adjusted R Square Std. Error of the Estimate .534a .285 .284 11.440 a. Predictors: (Constant), no, AGE OF RESPONDENT, yes, HIGHEST YEAR OF SCHOOL COMPLETED b. Dependent Variable: Rs occupational prestige score (2010) ANOVAa Model Sum of Squares df Mean Square F Sig. Regression 126088.636 4 31522.159 240.867 .000b Residual 316050.099 2415 130.870 Total 442138.735 2419 a. Dependent Variable: Rs occupational prestige score (2010) b. Predictors: (Constant), no, AGE OF RESPONDENT, yes, HIGHEST YEAR OF SCHOOL COMPLETED Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta (Constant) 6.194 1.326 4.671 .000 AGE OF RESPONDENT .112 .014 .143 8.277 .000 HIGHEST YEAR OF SCHOOL COMPLETED 2.324 .078 .525 29.896 .000 yes -.335 .473 -.012 -.709 .478 no 2.487 1.397 .032 1.780 .075 a. Dependent Variable: Rs occupational prestige score (2010) Residuals Statisticsa Minimum Maximum Mean Std. Deviation N Predicted Value 10.02 62.23 43.65 7.220 2420 Residual -40.393 40.169 .000 11.430 2420 Std. Predicted Value -4.659 2.573 .000 1.000 2420 Std. Residual -3.531 3.511 .000 .999 2420 a. Dependent Variable: Rs occupational prestige score (2010) Frankfort-Nachmias, C., & Leon-Guerrero, A. (2015). Social statistics for a diverse society (7th ed.). Thousand Oaks, CA: Sage Publications.  Wagner, W. E. (2016). Using IBM® SPSS® statistics for research methods and social science statistics (6th ed.). Thousand Oaks, CA: Sage Publications.

## Hello, I need help solving this excel problem for business analysis. If I could have it done by 10pm tonight so I could review it that would be great. Thank you!

Hello, I need help solving this excel problem for business analysis. If I could have it done  by 10pm tonight so I could review it that would be great. Thank you!

Hello, I need help solving this excel problem for business analysis. If I could have it done by 10pm tonight so I could review it that would be great. Thank you!