## MGT2250 Role of Statistics

MGT2250 Role of Statistics.

Do you know what Mark Twain said about statistics?
In his autobiography he once wrote: “There are three kinds of lies: lies, damned lies and statistics.”

On two-three pages , write an essay (double spaced) that explains the important role statistics plays in driving modern world. How does statistics help managers assess the credibility and usefulness of information? How can it help them make decisions that lead to the most optimal outcomes? Please address these questions in your essay.
You are encouraged to be as creative as possible; for example, you may use well-known quotes, that are contrary to the Twain quote above, to support your points. Humorous references are welcome, as well. Just be sure to include all of your references used at the end of your essay.

MGT2250 Role of Statistics

## South University Statistical Software Applications Discussion

South University Statistical Software Applications Discussion.

### Discussion Question

Using the Excel Sheet and descriptive statistics page; you will write up your analysis for the 20 participants.

This week, you learned about the
statistical software applications used to analyze data for research
analysis. For this week’s discussion, you will use Excel sheet provide
to run descriptive statistics, create graphs and respond to the
following:

• How could you use Excel descriptive statistics for data analysis research?
• What are your plans for learning more about Excel and how will the
analysis of research data?

Refer to this week’s readings and video tutorials before starting this two part discussion question assignment.

Step 1: Entering Data

### Open a blank worksheet in the Excel program

You will now use Excel to view a sample dataset

### Dataset Options

In many cases, researchers may have the
data from their study in another software package like Microsoft Excel.
However, if the data is not available in a software spreadsheet you can
manually enter the data. Option 2: Manual Data Entry

In the Worksheet window, type “Age” in C1.
Enter the numbers as shown in the dataset below. Enter the remaining
data as shown below (set up your column labels i.e., variable). The
measure reflects math anxiety and the study variables (cringe, uneasy,
afraid, worried, understand) the math anxiety range is from 1–5 with low
being the least and 5 the highest.

 Age Cringe Uneasy Afraid Worried Understand 28 5 3 4 4 3 34 2 5 3 2 1 25 4 4 4 2 5 56 3 4 3 1 2 23 5 4 3 3 4 29 1 5 3 2 3 30 3 3 5 2 5 59 2 5 5 1 2 45 4 2 5 3 3 38 1 2 4 1 1 33 3 2 4 3 2 47 4 2 3 4 5 24 1 5 3 4 4 29 5 4 2 1 3 53 3 1 5 2 1 48 4 4 1 5 3 27 2 5 4 3 4 34 4 4 3 2 5 26 4 5 2 3 2 36 5 5 5 4 3

Step 2: Click on Excel tab for Add
Ins; if you do not see statistics; you will need to open the file
option; click on Add ins; click on ok; a box will open which will allow
you to choose Statistics package; place a check mark in the box and
click ok. How to Run Descriptive Statistics

Now that your data is in Excel, you will
look at the descriptive statistics for this dataset. Select the data in
all the columns except the top that has words for the columns; however
you have the file already completed and a picture of the descriptive
statistics..See end of page for a copy of the excel sheet and
descriptive statistics output.

### Discussion Question Part 1

How could you use Excel descriptive
running descriptive statistics. Use the results in the Session Window to
you learn writing up your analysis.

Step 3: Excel and Graphs

You will now look at graphing. Select
insert graph located at the top of the sheet; highlight the data you
want to use for a chart; select the type of chart; select ok. Try using
the histogram feature for one of the variables and select “Ok”. You can
create other Histogram graphs by choosing different variables. You can
also choose from the other ten graph choices shown on the insert chart
function.

### Discussion Question Part 2

of benefit in your future analysis of research data? Copy and paste your
graph(s) in a Word document and attach to your discussion response.

South University Statistical Software Applications Discussion

## Wk 11 Categorical Data Analysis & Testing for Bivariate Categorical Analysis

Wk 11 Categorical Data Analysis & Testing for Bivariate Categorical Analysis.

To prepare for Part 1:

• Review Chapters 10 and 11 of the Frankfort-Nachmias & Leon-Guerrero course text and the media program found in this week’s Learning Resources related to bivariate categorical tests.
• Create a research question using the General Social Survey dataset that can be answered using categorical analysis.

#### By Day 3

Use SPSS to answer the research question. Post your response to the following:

1. What is your research question?
2. What is the null hypothesis for your question?
3. What research design would align with this question?
4. What dependent variable was used and how is it measured?
5. What independent variable is used and how is it measured?
6. If you found significance, what is the strength of the effect?
7. Explain your results for a lay audience and further explain what the answer is to your research question.

Be sure to support your Main Post and Response Post with reference to the week’s Learning Resources and other scholarly evidence in APA Style.

To prepare for Part 2:

• Review Chapters 10 and 11 of the Frankfort-Nachmias & Leon-Guerrero course text and the media program found in this week’s Learning Resources related to bivariate categorical tests.
• Using the SPSS software, open the Afrobarometer dataset found in this week’s Learning Resources.
• Next, review the Chi Square Scenarios found in this week’s Learning Resources and consider each research scenario for this Assignment.
• Based on the dataset you chose and for each research scenario provided, using the SPSS software, choose a categorical data analysis and run a sample test.
• Once you perform your categorical data analysis, review Chapter 11 of the Wagner text to understand how to copy and paste your output into your Word document.

For this Assignment:

Write a 1- to 2-paragraph analysis of your categorical data results for each research scenario. 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.

Use proper APA format, citations, and referencing for your analysis, research question, and display of output.

Wk 11 Categorical Data Analysis & Testing for Bivariate Categorical Analysis

## Health Information Technology Electronic Prescribing In Healthcare

Health Information Technology Electronic Prescribing In Healthcare.

Health Informatics/IT, visit the Health Information Technology: Key Topics (Links to an external site.)Links to an external site. website.

1. Choose one of the topics listed.
2. Click on the topic and explore the information provided.

Using the information accessed from this site, write a four- to five-page paper in which you assess this information and discuss your reactions and opposing viewpoints on the issues. The paper must be in APA style and utilize a minimum of three-four scholarly and/or peer-reviewed
sources that were published within the last five years. .

Health Information Technology Electronic Prescribing In Healthcare

## BHS220 Trident Drawing Inferences About Population Means & Proportions

BHS220 Trident Drawing Inferences About Population Means & Proportions.

Having developed the null and alternative hypotheses in the previous module, write a (2-3 pages) paper in which you:

1. Identify a test statistic to help you assess the evidence against the null hypothesis you developed in the previous module.
2. Explain why you have chosen the specific test statistic. Include in your discussion description of the test statistic.
3. Summarize your findings by creating a summary graph in which you display your data.
4. Discuss the total number of measurements (sample size), the possibility for measurement error, and whether it is large enough to paint an accurate picture.

BHS220 Trident Drawing Inferences About Population Means & Proportions

## Week 4 Weather Conditions Element Variable or Observation Midterm

Week 4 Weather Conditions Element Variable or Observation Midterm.

# Midterm

There are 8 questions in total, each worth 12.5 points. Please upload your answers to the dropbox. The Grantham Late policy applies to the midterm, and it is a 5% deduction per late day. Remember that work is required. That work may be calculations, a computer printout, an Excel program – but there has to be something that shows where numbers came from. This midterm may only be taken one time.

Question 1

The following shows the temperatures (high, low) and weather conditions in a given Sunday for some selected world cities. For the weather conditions, the following notations are used: c = clear; cl = cloudy; sh = showers; pc = partly cloudy. 1. Is “condition” an element, variable, or observation?
2. Provide the observation for Mexico City.
3. Give an example of a quantitative variable.
4. Provide the range for the low temperature.
5. What is the mode for the high temperature?
6. Explain why the “lo” is not ordinal.

Question 2

A student has completed 16 courses in the School of Arts and Sciences. Her grades in the 16 courses are shown below.

 D D C D A B F A A A C B B C C D
1. Develop a frequency distribution table for her grades.
2. Create a bar chart for her grades. Remember the importance of good titles and labeled axes.
3. All the courses are three credits except for the two that are highlighted. They are science courses and are worth 5 credits each. Using a weighted mean, calculate the student’s grade point average. A = 4.0; B= 3.0; C= 2.0; D =1.0; F = 0

Question 3

The number of hours worked per week for a sample of ten students is shown below.

 Student Hours 1 33 2 40 3 15 4 25 5 15 6 30 7 32 8 10 9 15 10 35
1. Determine the mean, median, and mode.
2. Explain which of the three values (mean, median, mode) is the best representation of central tendency in this particular set of data. (This is not an “in general” question.)
3. What is the standard deviation for the number of hours worked? What does standard deviation tell us?
4. Create a histogram for this data. Discuss whether or not this data is normally distributed. Justify your answer.

Question 4

You are given the following information on Events A, B, C, and D.

P(A) = .5

P(B) = .3

P (C) = .20

P(A U D) = .8

P(A ∩ C) = 0.05

P (A │B) = 0.22

P (A ∩ D) = 0.25

1. Compute P(D).
2. Compute P(A ∩ B).
3. Compute P(A | C).
4. Compute the probability of the complement of C.
5. What does it mean to be mutually exclusive? Give an example.

Question 5

When a particular machine is functioning properly, 80% of the items produced are non-defective.

1. If seven items are examined, what is the probability that three are defective?
2. If seven items are examined, what is the probability at at least three are non-defective?
3. If seven items are examined, what is the probability that at most, one is defective?
4. What is the expected number of defective items if ten items are examined?

Question 6

The average starting salary of this year’s graduates of a large university (LU) is \$34,000 with a standard deviation of \$7,000. Furthermore, it is known that the starting salaries are normally distributed.

1. What is the probability that a randomly selected LU graduate will have a starting salary of at least \$32,000?
2. Individuals with starting salaries of less than \$19,900 receive a low income tax break. What percentage of the graduates will receive the tax break?
3. What percent of graduates will have their salaries one standard deviation from the mean?
4. What is the range of salaries that is one standard deviation from the mean?
5. What is the range of salaries that are two standard deviations from the mean?

Question 7

A simple random sample of 8 computer programmers revealed the sex of the programmers and the following information about their weekly incomes.

 Programmer Weekly Income Sex A \$550 M B \$654 M C \$911 F D \$500 M E \$727 M F \$688 F G \$1000 F H \$892 M
1. If all the salaries were written on separate pieces of paper, and one was drawn at random, what is the probability that the one that was drawn would be over \$700?
2. If a programmer were selected at random to complete a project, what would the probability be that the programmer was male?
3. What is the probability of selecting an income of under \$700 per week given that a male was selected?
4. If all the salaries with the name of who earned it were written on separate pieces of paper and two were drawn at random (the first one was NOT returned to the pile), what is the probability that both were female?
5. If all the salaries with the name of who earned it were written on separate pieces of paper and two were drawn at random (the first one was NOT returned to the pile), what is the probability that the first draw would be the salary of a male and the second would be one of a female?

Question 8

Students of a large university spend an average of \$7 a day on lunch. The standard deviation of the expenditure is \$2. A simple random sample of 25 students is taken.

1. What is the probability that the sample mean will be at least \$4?
2. Jason spent \$15 on his lunch. Explain, in terms of standard deviation, why his expenditure is not usual.
3. Explain what information is given on a z table. For example, if a student calculated a z value of 2.77, what is the four-digit number on the z table that corresponds with that value? What exactly is that 4-digit number telling us?
4. Explain why we use z formulas. Why don’t we just leave the data alone? Why do we convert?
 Grading Criteria Assignments Maximum Points Meets or exceeds established assignment criteria 40 Demonstrates an understanding of lesson concepts 20 Clearly presents well-reasoned ideas and concepts 30 Uses proper mechanics, punctuation, sentence structure, and spelling 10 Total 100

Week 4 Weather Conditions Element Variable or Observation Midterm

## Week 5 Students Watching TV Margin of Error Statistics Questions

Week 5 Students Watching TV Margin of Error Statistics Questions.

17. Picture below

18. Picture below, there are two parts. do part 1 first and I can add part 2 to the messages after

19. Picture below, there are two parts. do part 1 first and I can add part 2 to the messages after

20. Estimate the minimum sample size needed to achieve the margin of error E =0.024 for a 95% confidence interval.

The minimum sample size is……? (Round to the nearest integer)

21. Researchers sample 7,000 households concerning TV shows they watch. Based on the sample 12% reported watching 60 Minutes. What is the 95% confidence interval for the proportion of all Americans that watch 60 Minutes?

The 95% confidence interval is the following.

<p< round to 3 decimal places as needed

22. Picture below. there are two parts. do part 1 first and I can add part 2 to the messages after

Week 5 Students Watching TV Margin of Error Statistics Questions

## GB 513 UOPX Unit 6 Real World Situations Business Analytics PPT & Excel Sheet

GB 513 UOPX Unit 6 Real World Situations Business Analytics PPT & Excel Sheet.

In this assignment, you will be assessed based on the following outcomes:

GB513-4: Evaluate real-world situations and present solutions using statistical methods.

PC-6.1: Incorporate data, inferences, and reasoning to solve problems.

This assignment has two parts. Part 1 has questions about forecasting, you will submit your answers to part 1 using the Unit 6 Assignment template (see attached).

You still need to submit the Excel file you used to generate your answers, in addition to the report in Word.

Part 2, requires you to analyze a case, you will prepare a PowerPoint presentation to present your findings. See further instructions below under “Part 2-Case Analysis” for more details.

Part 1 – Forecasting

Answer the following three questions using the template provided.

# Question 1

A store managers wishes to forecast the weekly number of television sets sold. Calculate the error for each of the following forecasts, the MAD and the MSE. Be sure to show the entire table in the work area of the template.

1202 — —

2191 202

3173 192

4169 181

5171 174

6175 172

7182 174

8196 179

9204 189

10 219 198

11 227 211

# Question 2

The data below shows the number of goods manufactured in one year.

(\$ billion).

Calculate forecasts for years 6 through 13 using a 5-year moving average.

Then, calculate forecasts for years 6 through 13 using a 5-year weighted moving average. Weight the most recent year by 6, the previous year by 4, the year before that by 2, and the other years by 1. Be sure to show the entire table in the work area of the template.

a)What is the forecast for year 13 based on the 5-year moving average?

b)What is the forecast for year 13 based on the 5-year weighted moving average?

c)What is the MAD for the moving average forecast?

d)What is the MAD for the weighted moving average forecast?

• Which forecasting model that you calculated is better? Why?
• What is the average rating for all CBC movies? How about ABN movies and BBS movies?
• Comment how the networks are performing, using the metrics in the table. Your analysis should extend beyond simply comparing the average ratings for each network.
• What are the null and alternative hypotheses (state in full sentences)?
• Which dependent variable contributes more when determining a movie’s rating: Being fact-based or having one star? How much does each of these factors change the ratings?
• How well does this regression analysis explain the ratings? Justify your answers referring to the relevant figures.
• Are either, both, or neither of the independent variables significantly related to the ratings at 95% confidence? Justify your answers referring to the relevant figures.
 Year Factory orders 1 2,512.70 2 2,739.20 3 2,874.90 4 2,934.10 5 2,865.70 6 2,978.50 7 3,092.40 8 3,052.60 9 3,145.20 10 3,114.10 11 3,257.40 12 3,654.00 13

# Question 3

The “Economic Report to the President of the United States” included data on the amounts of manufacturers’ new and unfilled orders in millions of dollars. Shown here are the figures for new orders over a 21-year period.

Use the charting tool in Excel to develop a regression model to fit the trend effects for the data. Use a linear model and then try a polynomial (order 2) model. Make sure the charts show the line formula and the r-squared value. Include both charts in your report. Then, answer the following question:

● How well does either model fit the data? Which model should be used for forecasting? Explain using the relevant metrics.

 Year Total Number of New Orders 1 55,022 2 55,921 3 64,182 4 76,003 5 87,327 6 85,139 7 99,513 8 115,109 9 116,251 10 121,547 11 123,321 12 141,200 13 162,140 14 168,420 15 171,250 16 176,355 17 195,204 18 209,389 19 237,025 20 272,544 21 293,475

Part 2 – Case Analysis

To answer Part 2, you will prepare a PowerPoint presentation to present your findings. Make sure you also submit the Excel file to show your work for Part 2. You will receive a 100 point reduction if you fail to include the Excel file showing your work for Part 2.

Place all calculations for each of the questions on a separate worksheet. Then, using the results of your work from Excel, prepare PowerPoint slides to answer the questions in a presentation format. All relevant content should be on the slides; do not use the notes section or leave information in the Excel file. The executives reviewing the presentation should not need to switch to another document to see the required information.

The data you need is provided to you in the Unit 6 Excel file in Course Documents. Make sure to use that file. Do not type anything in manually or download anything from the Internet.

You will be analyzing the “Colonial Broadcasting” case in the course pack that you bought at the beginning of the course. Begin by reading the description in the case. Then, answer the questions listed below, NOT the questions listed in the case. Ignore everything in the case document after the end of page 4.

The executives at CBC want to see how they are doing in ratings against the other networks and how the ratings will continue to change in the upcoming months. They also want to know if hiring stars makes a difference and the impact of fact-based programming compared to hiring stars. Remember that your audience is the management of CBC. Therefore, make sure your presentation is professional and provides sufficient explanation.

b.Include a table that shows the average and the other descriptive statistics (using the data analysis tool pack in Excel) for the ratings of the three networks (one column for each network). Explain what you learn from each of the metrics in the table.

2.Create a line graph of the monthly average ratings for CBC for the year. Note that there are multiple ratings data for the months; you will need to calculate an average for each month first, and then plot the averages. After you create the graph, fit a linear trend line, displaying the formula and the r-squared. Explain to the executives if you can use this time series data to forecast the ratings of upcoming months. How accurate can you expect this forecast to be?

3.Should the CBC hire stars for their movies? To answer this question, run a hypothesis test to see if there is a significant difference between the ratings of movies with stars versus movies without stars. Use the data for CBC movies only. Use 95% confidence.

b.Run the test using Excel and include the output table. Use a t-test assuming equal variances.

4.Run a multiple regression where the dependent variable is ratings and the independent variables are star and fact. Use data from CBC only. CBC Management has several questions:

Be sure to complete the Unit 6 Assignment template. Submit your assignment to the Unit 6 AssignmentDropbox.

 Unit 6 Assignment Content Points Possible Points Earned Part 1 – Forecasting Question 1 Provided the MAD. 5 Question 1 Provided the MSE. 5 Question 2a Correct forecast for year 13 using a 5-year moving average. 5
 Question 2b Correct forecast for year 13 using a 5-year weighted moving average. 5 Question 2c Correct MAD for moving average forecast. 5 Question 2d Correct MAD for weighted moving average forecast. 5 Question 2e Recommended the better model with justification. 5 Question 3 Used Excel charting to fit a linear trendline, including the formula and r-squared. 5 Question 3 Used Excel charting to fit a polynomial trendline, including the formula and r-squared. 5 Question 3 Recommended the better model with justification. 5 Part 2 – Case Analysis Question 1 Correct average rating for all three networks. 10 Question 1 Correct table showing the average and other descriptive statistics for the ratings of the three networks, using one column for each network. 10 Question 1 Appropriate explanation and analysis of what is learned from each of the metrics in the descriptive statistics table. 20 Question 2 Correct line graph using the calculated average monthly ratings of CBC for the year, showing r-squared and the formula. 20 Question 2 Summary to executives regarding whether the linear forecast can be used to project ratings, including an assessment of how accurate the forecast can be expected to be. 20 Question 3 Correct null and alternative hypotheses stated in full sentences. 20 Question 3 Accurate hypothesis test results. 20 Question 3 Correct recommendation and justification for whether CBC should hire stars. 20 Question 4 Correct figures and explanation of how much contribution each independent variable makes when determining a movie’s rating: 20 Question 4 Correct figures and explanation of how well this regression analysis explains the ratings. 20 Question 4 Correct figures, accurate identification and justification of which variables are significantly related to ratings. 20 PowerPoint is formatted appropriately and communicated clearly. 50 Total 300

GB 513 UOPX Unit 6 Real World Situations Business Analytics PPT & Excel Sheet

## STATS 120C University of California Irvine Probability Statistics Questions

STATS 120C University of California Irvine Probability Statistics Questions.

1. Suppose we have the following unbalanced two-way ANOVA modeliid 2 yijk =μijijijk εijk N(0,σ )

where i = 1, 2, 3 and j = 1, 2 denote, respectively, the number of levels for factor A and the number of levels for factor B. Suppose that the number of observations (Ki j ) per group is: Factor B FactorA j=1 j=2

i=145i=234i=343

e.g. we have recorded 4 observations at level 1 of factor A and level 1 for factor B, 5 observations at level 1 of factor A and level 2 for factor B, etc.

1. (a) State explicitly what are the constraints imposed on the αi’s, the βj’s and the δi j ’s by the two-way ANOVA model in this situation.
2. (b) Provide an interpretation of the two-way ANOVA parameters αi, βjand δi j in a way that is understandable by a non-statistician.
3. (c) DerivetheMLE’softhetwo-wayANOVAparametersμ,α1,α2,α3,β1,β2,δ11,δ21,…,δ32

2. Suppose that the following data represent the units of production turned out each day by 3 different machinists, each working on the same machine for three different days:        Machine

1. B1 15,15,17
2. B2 17,17,17
3. B3 15,17,16
4. B4 18,20,22

Machinist B 19,19,16 15,15,15 18,17,16 15,16,17

A

C 16,18,21 19,22,22 18,18,18 17,17,17  Using a 0.05 level of significance, test whether

1. (a) the four machines resulted in the same average production amount
2. (b) the machinist yield the same average production amount
3. (c) the effect of the machine on the average production amount does not depend on the machinist

For each of the tests above: state the null and alternative hypothesis, report the value of the test statistic (show how you obtained it), report the p-value, state your decision and state your conclusion.

STATS 120C University of California Irvine Probability Statistics Questions

## Rasmussen College Module 6 Correlations and Regression Analysis Excel Task

Rasmussen College Module 6 Correlations and Regression Analysis Excel Task.

## Competency

Determine and interpret the linear correlation coefficient, and use linear regression to find a best fit line for a scatter plot of the data and make predictions.

## Scenario

According to the U.S. Geological Survey (USGS), the probability of a magnitude 6.7 or greater earthquake in the Greater Bay Area is 63%, about 2 out of 3, in the next 30 years. In April 2008, scientists and engineers released a new earthquake forecast for the State of California called the Uniform California Earthquake Rupture Forecast (UCERF).

As a junior analyst at the USGS, you are tasked to determine whether there is sufficient evidence to support the claim of a linear correlation between the magnitudes and depths from the earthquakes. Your deliverables will be a PowerPoint presentation you will create summarizing your findings and an excel document to show your work.

Concepts Being Studied

• Correlation and regression
• Creating scatterplots
• Constructing and interpreting a Hypothesis Test for Correlation using r as the test statistic

that contains the following information:

• Magnitude measured on the Richter scale
• Depth in km

Using the spreadsheet, you will answer the problems below in a PowerPoint presentation.

## What to Submit

The PowerPoint presentation should answer and explain the following questions based on the spreadsheet provided above.

• Slide 1: Title slide
• Slide 2: Introduce your scenario and data set including the variables provided.
• Slide 3: Construct a scatterplot of the two variables provided in the spreadsheet. Include a description of what you see in the scatterplot.
• Slide 4: Find the value of the linear correlation coefficient r and the critical value of r using α = 0.05. Include an explanation on how you found those values.
• Slide 5: Determine whether there is sufficient evidence to support the claim of a linear correlation between the magnitudes and the depths from the earthquakes. Explain.
• Slide 6: Find the regression equation. Let the predictor (x) variable be the magnitude. Identify the slope and the y-intercept within your regression equation.
• Slide 7: Is the equation a good model? Explain. What would be the best predicted depth of an earthquake with a magnitude of 2.0? Include the correct units.
• Slide 8: Conclude by recapping your ideas by summarizing the information presented in context of the scenario.

Along with your PowerPoint presentation, you should include your Excel document which shows all calculations.