# MHA610 Introduction to Biostatistics Assignments and DQs

MHA610 Introduction to Biostatistics Assignments and DQs

MHA610 Introduction to Biostatistics Assignments and DQs

Course Guide

This course explores the application of fundamental statistical methods to the healthcare environment. Course content includes both descriptive and inferential methods including: data analysis, statistical estimation, regression analysis, analysis of variance, hypothesis testing, and analysis of longitudinal data.

Note: This course uses software that is not Mac OS compatible. Access to a Windows PC or a Windows-based platform is required.

Table of Contents

Course at a Glance

Course Description

This course explores the application of fundamental statistical methods to the healthcare environment. Course content includes both descriptive and inferential methods including: data analysis, statistical estimation, regression analysis, analysis of variance, hypothesis testing, and analysis of longitudinal data.

Course Design

The purpose of this course is to provide an introduction to statistics relating to health care research. Students will be introduced to various health data sources, and will proceed to analyze, assess, and evaluate these data using basic statistical concepts and methodology. Students will learn how to use statistical software in order to obtain and interpret descriptive and inferential statistical results.

Students will also learn basic principles of probability theory and how to draw conclusions from available data utilizing statistical tools, assessing whether observed statistics could occur by chance alone. Notions of probability are of fundamental importance, and students will utilize both frequentist and Bayesian probability concepts in their evaluations.

Statistics not only plays a crucial role in undertaking and interpreting research in the health sciences, but also arises in quotidian settings. For example, what does it mean to have a 20% chance of precipitation today? At the conclusion of this course, the students increased understanding of statistics and probability will empower them in their studies, their work, and their daily lives.

Prerequisites

There are no prerequisites for MHA610.

Course Learning Outcomes

Upon successful completion of this course, students will be able to

Apply basic statistical principles for describing, analyzing, and interpreting health

Apply statistical methods of estimation and hypothesis testing in biostatistics and

Analyze relationships between quantitative variables using correlation and linear

Evaluate health care delivery and services using epidemiological data and appropriate statistical

Communicate the findings and implications from statistical analyses to health care

Course Materials

Required Text

Triola, M. M., & Triola M. F. (2006). Biostatistics for the biological and health sciences. Boston, MA: Pearson Education, Inc.

Triola, M. M., & Triola M. F. (2006). [Student companion website].

Boston, MA: Pearson Education, Inc. Retrieved from:

The software and data sets for the course may be accessed through

Note: This course uses software that is compatible with both Mac and Windows-based platforms. In addition, Microsoft Excel and Word will be used extensively throughout the course.

Required Resources

Supplemental Materials

Koziol, J. (2014). (2014). [PDF]. College of Health, Ashford University: San Diego, CA.

Websites

Centers for Disease Control. (2014). . Retrieved from

Centers for Disease Control and Prevention. (2014). Retrieved from

(2012). Retrieved from by-age-and-gender

Recommended Resources

Multimedia

Koziol, J. (Producer). (2014). [Video file]. Retrieved from

Koziol, J. (Producer). (2014). [Video file]. Retrieved from

Koziol, J. (Producer). (2014). [Video file]. Retrieved from

Koziol, J. (Producer). (2014). [Video file]. Retrieved from

Koziol, J. (Producer). (2014). [Video file]. Retrieved from

Koziol, J. (Producer). (2014). [Video file]. Retrieved from

Koziol, J. (Producer). (2014). [Video file]. Retrieved from

Koziol, J. (Producer). (2014). [Video file]. Retrieved from

Koziol, J. (Producer). (2014). [Video file]. Retrieved from

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Course Grading

Multiple measures of assessment are used in the course, allowing students opportunities to demonstrate their learning in more than one way and giving consideration to individual learning styles. Course components that will be assessed include:

Discussions

Each week students will participate in online discussions with classmates, which are related to the weeks readings. These discussions replace the interactive dialogue that occurs in the traditional classroom setting. Each week, students initial discussion posts are due by 11:59 p.m. (in the time zone in which each student resides) on Day 3 (Thursday). Students will have until 11:59 p.m. on Day 7 (the following Monday) to make the required minimum number of response posts to classmates. Discussions represent 26% of the overall course grade.

Quizzes

In Weeks Three and Six, students will demonstrate and reinforce their understanding of the weeks content by taking open-book quizzes. There is no time limit to complete the quiz, and each quiz can be taken two times. The quiz must be completed in one sitting, by Day 6 of the week in which it is due. The questions are multiple choice and true/false. Each quiz is worth 5 percent. Quizzes represent 16% of the overall course grade.

Assignments

There are written assignments due in Weeks One through Five of this course. These assignments must reflect college- level writing. Assignments represent 40% of the overall course grade.

Final Project

The final assignment for this course is a Final Project. The purpose of the Final Project is for you to culminate the learning achieved in the course by taking a new approach to the datasets that you have looked at throughout the course. The Final Project represents 18% of the overall course grade.

Grading Percent Breakdown

Activity

Grading Percent

Discussions 26

Quizzes 16

Assignments 40

Final Project 18

Total 100

Week One

Course Content

To be completed during the first week of class

Overview

Activity Due Date Format Grading Percent

Post Your Introduction Day 1 Discussion 2

Hospital Data Day 3 (1st post) Discussion 4

U.S. Mortality Rates Histogram Day 7 Assignment 8

Weekly Learning Outcomes

This week students will

Calculate summary statistics from

Create appropriate graphs and charts for nominal and ordinal

Introduction

During Week One, you will be introduced to quantitative (continuous) and qualitative (discrete or categorical) data. You will learn appropriate graphical techniques for displaying and summarizing both types of data. You will learn about descriptive statistics for location (i.e., mean, median) and scale (i.e., standard deviation, range), for reporting purposes. You will begin to learn fundamentals of probability theory.

Required Resources

Text

Triola, M.M., & Triola, M.F. (2006). Biostatistics for the Biological and Health Sciences. Boston, Ma: Pearson Education, Inc.

Chapter 1: Introduction

After reading the chapter, review your grasp of the material in Chapter 1 by solving the odd- numbered questions in the Review Exercises and the Cumulative Review Exercises at the end of Chapter 1. Solutions to these problems are given at the end of the

Chapter 2: Describing, Exploring, and Comparing Data

After reading the chapter, review your grasp of the material in Chapter 2 by solving the odd- numbered questions in the Review Exercises and the Cumulative Review Exercises at the end of Chapter 2. Solutions to these problems are given at the end of the

Triola, M. M., & Triola M. F. (2006). [Student companion website].

Boston, MA: Pearson Education, Inc. Retrieved from:

Supplemental Materials

Koziol, J. (2014). MHA610_Week 1_Discussion_Hospital data [Excel file].

Koziol, J. (2014). MHA610_Week 1_Discussion_Hospital data [Statdisk file].

Website

World Life Expectancy. (2012). Retrieved from

This website houses the data that will be used for the U.S. Mortality Rates histogram assignment for this week.

Recommended Resources

Multimedia

Koziol, J. (Producer). (2014). MHA610 Week 1 Assignment (Part 1) [Video file]. Retrieved from

Koziol, J. (Producer). (2014). [Video file]. Retrieved from

Koziol, J. (Producer). (2014). [Video file]. Retrieved from

Koziol, J. (Producer). (2014). [Video file]. Retrieved from

These screencasts help explain the Week One

Discussions

Participate in the following discussions:

Post Your Introduction. 1st Post Due by Day 1. Post a brief introduction on the first day of class. Share any past experiences (academic or professional) that you have had with epidemiology, biostatistics, or

health data analysis. What topic are you most interested in as it relates to epidemiology and biostatistics? Briefly explain why you are interested in this topic. Additionally, describe what you are looking forward to learning in this course.

Guided Response: Review several of your classmates posts. Welcome at least three of your peers to this course. What similarities in experience did you note between you and your classmate? Did your colleagues description of his or her topic of interest differ from your own? If so, did the description spark your interest in that topic as well? If so, how? Introduction should be at least 250 words in APA format.

Hospital Data. 1st Post Due by Day 3. The MHA610_Week 1_Discussion_Hospital Data Excel file (available in the classroom) and MHA610_Week 1_Discussion_Hospital Data Statdisk file (available in the classroom) contains basic demographic information on 250 patients admitted to a community hospital over a two week period. The first row of the worksheet indicates the variable names:

Gender Male (M) or female (F)

Ethnicity

SevIllnessCode These are All Patient Refined Diagnosis Related Groups (APR-DRG) categories of severity of illness, ranging from:

SevIllnessDescr Mild (Category 1) to extreme (Category 4)

Age In years

Wt Patient weight in kilograms

Ht Patient height in centimeters

BMI Patient body mass index (BMI) where BMI = wt/ht*2, with weight in kilograms and height in meters

APR-DRG Denotes All Patient Refined Diagnosis Related Group, a widely used inpatient classification system.

For this discussion, describe and summarize the demographic information on these patients. You may use tables or graphs (or both) for this purpose. Your goal is to convey to the reader an accurate snapshot of these patients. Support your response with correct scholarly sources. You initial post must be at least 250-500 words.

Guided Response: Respond to at least two of your peers by Day 7, 11:59PM. Review your colleagues summary of the data. Did the method of presentation provide you with any new insights? If so, what are they? If not, what suggestions might you make to your colleague that could improve his or her representation of the data? All initial and peer postings should be at least 250-500 words in APA format supported by scholarly sources. MHA610 Introduction to Biostatistics Assignments and DQs

Assignment

U.S. Mortality Rates. Due by Day 7. Examine the burden of disease in the United States to provide important information on which parameter is to base decisions on public health priorities.

To do this, we will utilize mortality data for the United States. In the first part of this assignment, you will download and examine mortality data for your home state.

Go to

Choose your home state under the Choose State option (panel on left hand side)

Select BOTH under the Choose gender option in the middle

Scroll down to the bottom of the page, and read the fine print to learn for which year the mortality data have been

Copy and paste the relevant mortality data into

Drag your mouse over all of the Cause of Death rows, (50 rows), right click, and select Copy,

Open Excel and paste your selection into Excel. You should have a spreadsheet with 50 row and 19 columns (Columns A-S).

For the first part of the assignment, you will prepare a histogram of the leading causes of death (regardless of age) in your state. Follow the steps below in order to prepare your histogram:

Sort the Data

The numbers of deaths, all ages, are given in Column

Select all the

Then, select Data>Sort>Sort by Column C, Values, largest to smallest. (Make sure that my data has headers is not

You now have the leading causes of death in your state in Column A (cause) and Column C (frequency).

If you already know how to draw a histogram in Excel, proceed to do so with Columns A and C, making sure to truncate the data to the 30 leading

If you do not know how to draw a histogram in Excel, heres one method:

Choose the Chart Wizard, chart type column, chart sub-type clustered column (Step 1).

Click Next for Step

At Step 2, Click the Series button, which will open a new

Click Add under Series,

Enter Causes of Death in the Name box;

Clear the Values box, then

Drag your mouse over the 30 largest frequencies for the Values; and,

Drag your mouse over the first 30 causes of death (Column A) for the Category (X) axis labels box.

Click Next, and youll be brought to the Chart Options

Add a suitable title (e.g., Leading Causes of Death, 2010, your state)

Label the Y axis Frequency.

Click Next, and place the histogram in a new

You now have a histogram with the leading causes of death for your state. This presents one picture of the burden of disease in your state, but it isnt the only picture. We shall now look at a different metric: years of life lost due to each cause.

To do this, we will assume that the average life span is 80 years, and we will calculate how many years of life are lost for each cause of death, according to the age at death.

Please note that the ages are in categories (0 14, 15 24, 25 34,
, 65 74, and 75+). For this exercise, we will assume that the average age of death is at the middlepoint of each of these intervals (eg., 7.5, 19.5, 29.5,
, 69.5, and 80 for the last age category respectively). For example, an individual death in the 15-24 (19.5) age group incurs equals 60.5 years of life lost (80-19.5 = 60.5).

To make this histogram, we will compute a new column of values, years of life lost for each cause of death. (This entails writing a simple formula in Excel for the calculation corresponding to the first row of data, then dragging the formula down that column. If you have never done this calculation before in Excel, consult the screencast for detailed instructions.)

Go back to the original Excel spreadsheet that contained your

Using the formula above, create a column that calculates the years of life lost.

Now, sort the data by the years of life lost column, in descending order, before drawing a histogram of the results.

Finally, create a histogram of the 30 leading causes of death, in decreasing order of years of life

Do not forget to label the y-axis and provide a title for the

You now have two histograms representing the burden of disease in your state. The first histogram orders the causes of death in terms of overall mortality, and the second orders causes of death in terms of years of life lost.

Create a report of your findings that contains both of the histograms. The report should be at least 250-500 words supported by scholarly resources and in APA format. Assume that your task is to assess and prioritize public health needs in your state, and you need to inform and persuade policy makers for improving the well-being of your states constituents. Describe which findings are most relevant for this.

You should also explain any methodological or data limitations that exist in either histogram. In particular, describe your conclusions would be altered if you were to refine your findings by reanalyzing mortality rates based on gender and race in addition to age. The assignment should be at least 500 words in APA format supported by scholarly sources.

Week Two

Course Content

To be completed during the second week of class

Overview

Activity Due Date Format Grading Percent

Game of Chance Day 3 (1st post) Discussion 4

Sex Ratios Day 7 Assignment 8

Weekly Learning Outcomes

This week students will

Calculate probabilities of events using fundamental notions and rules of probability

Apply the binomial distribution to discrete data

Apply the Poisson distribution to discrete data

Introduction

In Week One, you were introduced to some fundamentals of probability. You will continue your exploration of probability theory in Week Two, including Bayes theorem for determination of posterior probabilities on the basis of prior and marginal probabilities. You will examine properties and parameterization of the two basic discrete probability distributions, the binomial and the Poisson. You will begin to use the binomial and Poisson distributions for inferential procedures.

Required Resources

Text

Triola, M.M., & Triola, M.F. (2006). Biostatistics for the Biological and Health Sciences. Boston, Ma: Pearson Education, Inc.

Chapter 3: Probability

After reading the chapter, review your grasp of the material in Chapter 3 by solving the odd-numbered questions in the Review Exercises and the Cumulative Review Exercises at the end of Chapter 3. Solutions to these problems are given at the end of the

Chapter 4: Discrete Probability Distributions

After reading the chapter, review your grasp of the material in Chapter 4 by solving the odd-numbered questions in the Review Exercises and the Cumulative Review Exercises at the end of Chapter 4. Solutions to these problems are given at the end of the

Triola, M. M., & Triola M. F. (2006). [Student companion website].

Boston, MA: Pearson Education, Inc. Retrieved from:

Supplemental Material

Koziol, J. (2014). (2014). [PDF]. College of Health, Ashford University: San Diego, CA.

This document provides an example that will be used in the Game of Chance discussion for this

Website

Center for Disease Control. (2014). Retrieved from

This website houses the data that will be used for the Sex Ratios assignment for this

Recommended Resources

Multimedia

Koziol, J. (Producer). (2014). MHA610 Week 2 Assignment (Part 1) [Video file]. Retrieved from

Koziol, J. (Producer). (2014). MHA610 Week 2 Assignment (Part 2) [Video file]. Retrieved from

These screencasts help explain the Week Two

Discussion

Participate in the following discussion:

Game of Chance. 1st Post Due by Day 3. For this discussion, select a game of chance, explain it briefly if it is likely to be unfamiliar to your classmates, then calculate probabilities of various outcomes like winning or losing

in this game. For example, you might choose your state lottery, scratch card game, a card game like poker, or a dice game like Craps or Yahtzee, as your game of chance.

As illustration, read a lottery analysis in

Guided Response: Respond to at least two of your classmates who chose a different game of chance than you by Day 7 at 11:59PM. Did your colleague provide enough explanation of the game to allow you to understand the analysis? Was the analysis provided by your classmate correct? If so, what optimal strategy for playing that particular game was described? If not, what suggestions would you make to your colleague to amend any issues?

Assignment

Sex Ratios. Due by Day 7. The normal male to female live birth sex ratio ranges from about 1.03 to 1.07. The sex ratio is defined as the ratio of male births to female births. You might expect boy and girl births to be equally likely, but in fact, baby boys are somewhat more common than baby girls.

Higher sex ratios are thought to reflect prenatal sex selection, especially among cultures where sons are prized more heavily than daughters. We will review sex ratios in the United States as a whole, as well as in individual states, to determine whether sex ratios vary significantly among various ethnic and racial groups.

To do this analysis, we will utilize natality data for the United States, provided by the Centers for Disease Control.

In the first part of the assignment, we will look at sex ratios for your home state, over the time period 1995 to 2002, by race. To obtain this information:

Go the

Click on Births under the WONDER Online Databases to bring you to the Natality Information screen

On this screen, click Natality for 1995-2002.

On the following screen, click I Agree in order to agree to abide by the government rules for data use (primarily, concerning confidentiality).

This will bring us to the Natality, 1995-2002 Request

In the block Organize table layout, group results by year, followed by race, and then gender.

In the block Select maternal residence, choose your state.

You can leave blocks 3 through 6 at their default values (i.e., All).

Click Send.

A new screen will open, with data (births) tabulated by Year, Race, and Gender.

Click Export, click Save, and a text file named Natality, _1995-2002 .txt or something similar will be downloaded onto your computer.

We can now process the downloaded data in Excel.

Load the text file into Excel. This will probably open the Text Import

Accept the defaults, and you should have a spreadsheet with the natality data

We will need to edit the data slightly before calculating sex ratios and drawing graphs of the sex ratios. To do this:

Scroll down to the end of the spreadsheet, and delete the rows with the extraneous information about the dataset. (This starts on or about row )

You may also delete the columns with headings Year CodeRace Code, and Gender Code since we will not be using them, however this is not

Next, sort the data, in order to delete some extraneous rows. Select the remaining columns, choose Data > Sort, then sort by Race in ascending

Scroll down to the end of the worksheet, and delete all rows with blanks for Race.

We will now add a new column to the worksheet for

Go to the first blank column in the worksheet: this column should be immediately to the right of a column labeled Births.

In the first row of this column, type Ratios.

Now, we will calculate different proportions of births, using formulas in excel. It is important to use excel to do the calculation, because it will allow you to quickly complete all of the

First, calculate the ratio of female births to total births for the American Indian race (female births/total births).

Next, calculate the ratio of male births to total births for the American Indian race (male births/total births).

Finally, calculate the ratio of male births to female births (male births/total births)

If you dont know how to do this calculation easily in Excel, please check out the screencast, which reviews

Once you have completed the first three cells in the ratio column, you can select them and copy

Select the remaining cells in the column and

You have now completed calculating all of the ratios, however, you may wish to double check to ensure that the formulas have adjusted for each

Once you have the Ratio column filled out, select that column, then Copy.

With the column still selected you want to select, click Paste Special and then Values. This will convert the formulas you entered to numbers, so they do not change when you do the next

Select all the columns, then Data>Sort>Notes in ascending order. We will be graphing the sex ratios for the years 1995 to 2002, by

Feel free to drop the two to four races that have the fewest numbers of births in your

Draw a line chart with markers with the year along the X-axis (we are looking at 1995 through 2002) and sex ratio along the Y-axis (with sex ratios typically between 1 and 1.1, though this may vary in your state).

If your version of excel has the Chart Wizard:

In step two of the Chart Wizard, choose the Series tab; in this window youll be adding all the information for the various

Under category (X) axis labels, drag your mouse over the cells 1995, 1996

For values, draw your mouse over the seven successive sex ratios for the particular racial group you chose; in the name box, enter the racial group; do this for each of the groups you want to display.

Select Next when you have finished with all the racial groups, and you will be brought to the Chart Options

Here, you can customize your graph, with a title and X and Y axis labels (i.e., your state births, year, and sex ratio respectively).

Continue with Next, and finish the

If your version of excel does not have the Chart Wizard, you will need to do some reformatting of your data before you can create a line chart. It is good practice to create a new worksheet in order to preserve your original

Your data should mimic the way you want your line chart to look. In this case, you want to create horizontal labels for each of the years (1995 through 2002) and vertical labels for each of the races. It should follow this format:

Year 1 Year 2 Year 3

Race A Ratio for Race A in Year 1 Ratio for Race A in Year 2 Ratio for Race A in Year 3

Race B Ratio for Race B in Year 1 Ratio for Race B in Year 2 Ratio for Race B in Year 3

After you have reformatted your data, select all of the data, then select Insert, then Line, then Line with Markers.

You should now have a line chart with each race having its own line, the ratios on the Y- axis, and the years on the X-axis.

You may wish to modify the Y-axis by right-clicking on it. Your upper and lower values on the axis should be just above and below your highest and lowest ratio

In a Word document, paste the graph you created (or, alternatively, submit your Excel workbook along with the Word document) and describe your findings, making sure to:

Summarize the sex ratios for each of the racial

Explain whether the sex ratios are relatively constant through the 1995 to 2002 period for all of the racial groups or if there are trends?

Explain any racial groups that have noticeably higher or lower sex ratios than other

Explain the conclusions you are drawing from your

In the second part of this assignment, you will undertake some formal statistical procedures with the natality data. We will repeat the previous steps, with some slight modifications.

Return to the

Click on Births under the WONDER Online Databases to get to the Natality Information

Select Natality for 2007 2012.

On the next screen, click I Agree in order to agree to abide by the government rules for data use (primarily, concerning confidentiality).

This will bring us to the Natality, 2007-2012 Request

In block Organize table layout, group results by race and then gender (not year).

In block Select maternal residence, choose your state.

You can leave block 3 at its default values (typically, All).

In block Select birth characteristics; select All Years under Year, and 1st child born alive to mother under Live Birth Order.

Blocks 5 and 6 can be left at their default

Click Send. A new screen will open, with data (births) tabulated by race and

Click Export, click Save, and a text file named Natality 2007-2012.txt (or something similar) will be downloaded onto your computer.

We have only four racial groups in this dataset: American Indians or Alaska Natives, Asian or Pacific Islanders, Black or African Americans, and Whites.

Using the normal approximation to the binomial distribution (without continuity correction), calculate z statistics for assessing whether the proportion of boys is .51 in each of the 4 racial groups, where n is the total number of births in a particular cohort, p = .51, q = 1 p = .49, and x is the number of boy births; z = ((x np) / sqrt(npq) ).

Under the null hypothesis that the proportion of boys should be 0.51, and under the normal approximation to the binomial distribution, the z statistics should have (approximately) standard normal distributions, (mean 0, standard deviation 1). Do any of the z statistics suggest that the proportion of boy births in any particular racial group differs significantly from .51?

Comment on your findings in your written report. Describe whether you think your results would change if we hadnt limited consideration to the first-born. This assignment should be at least 250-500 words in APA format supported by scholarly sources.

Week Three

Course Content

To be completed during the third week of class

Overview

Activity Due Date Format Grading Percent

Confidence Intervals Day 3 (1st post) Discussion 4

Week Three Quiz Day 6 Quiz 8

Immune Responses Day 7 Assignment 8

Weekly Learning Outcomes

This week students will

Apply the normal distribution to continuous data

Explain the use of statistical estimators in practice.

Construct confidence intervals for sample

Introduction

In Week Two, you examined two fundamental discrete probability distributions, the binomial and the Poisson. In this week, you will be introduced to the fundamental continuous probability distribution, the normal or Gaussian. You will learn how the normal distribution is parameterized by the mean and the variance, and how to undertake probability calculations based on the normal distribution. You will be introduced to the central limit theorem, and how it relates to the normal distribution.

You will also learn about sampling distributions (especially, the t distribution), and properties of estimators. Estimation is a key concept in statistics, and you will learn how to construct confidence intervals for sample estimators. You will learn about planning of experiments, for which sample size and power are fundamental notions.

Required Resources

Text

Triola, M.M., & Triola, M.F. (2006). Biostatistics for the Biological and Health Sciences. Boston, Ma: Pearson Education, Inc.

Chapter 5: Normal Probability

After reading the chapter, review your grasp of the material in Chapter 5 by solving the odd- numbered questions in the Review Exercises and the Cumulative Review Exercises at the end of Chapter 5. Solutions to these problems are given at the end of the

Chapter 6: Estimates and Sample Sizes with One

Review your grasp of the material in Chapter 6 by solving the odd-numbered questions in the Review Exercises and the Cumulative Review Exercises at the end of Chapter 6. Solutions to these problems are given at the end of the

Triola, M. M., & Triola M. F. (2006). [Student companion website].

Boston, MA: Pearson Education, Inc. Retrieved from:

Supplemental Materials

Koziol, J. (2014). MHA610_Week 3_Assignment_Data [Excel file].

Koziol, J. (2014). MHA610_Week 3_Assignment_Data [Statdisk file].

Recommended Resources

Multimedia

Koziol, J. (Producer). (2014). MHA610 Week 3 Assignment (Part 1) [Video file]. Retrieved from

Koziol, J. (Producer). (2014). MHA610 Week 3 Assignment (Part 2) [Video file]. Retrieved from

These screencasts help explain the Week Three

Discussion

Participate in the following discussion:

Confidence Intervals. 1st Post Due by Day 3. In this discussion, we will investigate confidence intervals for binomial probabilities. The discussion is in two parts.

Return to the data you had generated in the second part of the Week Two assignment. You should have total numbers of first-born boys and girls in your state between the years 2007 and 2012 separately by racial group: American Indians or Alaska Natives, Asian or Pacific Islanders, Black or African Americans, and Whites. For the first part of this discussion, construct and report the 95% confidence intervals for the proportions of first-born boys, separately for each racial group. (Use the normal approximation to the binomial distribution.) Comment on the confidence intervals: can you infer from the confidence intervals that the proportions of first-born boys differ among the racial groups? Explain what the widths of the confidence intervals tell

Leading up to elections, you often hear results of polls of voters preferences, with statements such as: This poll was taken from a random sample of 600 potential voters, and has an accuracy exceeding 96%. You may want to interpret the accuracy statement in terms of margin of error, as explained in the text, Section 6-2. Remember, the width of a confidence interval is a measure of the precision of the estimate

Guided Response: Respond to at least two of your peers by Day 7, 11:59PM. Consider the 95% confidence intervals your colleague pre