Elementary Statistics Picturing The World5th Editionby Larson Farbe ✓ Solved
Elementary Statistics: Picturing the World 5th Edition by Larson & Farber © 2011 Pearson You can access the textbook pages via the links in the Assignments pages. MyStatLab MyStatLab (MSL) is included with your course. You will access MSL using the links in the weekly Assignment pages. Course Description Students in this course are expected to master the tools used for statistical analysis and decision-making in business. This course includes descriptive statistics concepts and inferential concepts used to draw conclusions about a population.
Statistical decision-making techniques are used with sample data to predict population parameters. Research techniques such as sampling and experimental design concepts are included for both single and multiple sample groups. Terminal Course Objectives DeVry University course content is constructed from curriculum guides developed for each course that are in alignment with specific Terminal Course Objectives. The Terminal Course Objectives (TCOs) define the learning objectives that the student will be required to comprehend and demonstrate by course completion. The TCOs that will be covered in detail each week can be found in the Objectives section for that particular week.
Whenever possible, a reference will be made from a particular assignment or discussion back to the TCO that it emphasizes. 1 Given a business situation word problem and/or case study, use an appropriate sampling method to determine a sample size. 2 Given a word problem or case study, and an accompanying data set which addresses a business situation such as daily demand or monthly sales, calculate numerical summaries including measures of central tendency such as mean and median and measures of variation including range and standard deviation. 3 Given a word problem or case study, and an accompanying data set that addresses a business situation such as daily demand or monthly sales, develop graphical presentations of the data including histograms and stem and leaf displays.
4 Given a business situation word problem or case study such as expected monetary value, utilize basic probability concepts to determine a course of action. 5 Given a business situation word problem or case study such as defective items or waiting lines, use discrete probability concepts to determine a course of action. 6 Given a business situation word problem or case study such as one dealing with processing time or quantity of fill, use the normal probability distribution to determine a course of action. 7 Given a business situation where a confidence interval is necessary, develop a confidence interval and use it to determine a course of action. 8 Given a business situation requiring a hypothesis test, determine the appropriate test method and use it to determine a course of action.
9 Given a business situation where linear regression is necessary, use a regression model to determine a course of action. 10 Given a business situation word problem or case study and an accompanying data set, determine a best-fit regression model for nonlinear and/or multiple independent variables, and assess the validity and utility of the model. 11 Given a business situation word problem or case study requiring a comparison/contrast of mean production times of three or more suppliers, create the source table, calculate the F statistic, determine the p value, and analyze the results. Course Specific Requirements Labs will give you an opportunity to demonstrate your mathematical, problem solving, analytical, and MiniTab skills to solve problems and apply statistical techniques to practical problems.
Labs will be graded as follows: Statistics (tables, calculations, accurate values) 15% Graphs (titles, labels, accuracy) 15% Analysis (interpretation, analysis discussion) 60% Organization (proper format, style, used template) 10% The labs provide real practice with data sets and will provide you with an opportunity to integrate the concepts with practice. The labs go beyond the questions in the text by requiring you to learn MiniTab for the purpose of statistical analysis. You will also be using your writing skills to provide a summary that analyzes and interprets the work that you have done. Each lab has a "template" that you should use to submit your results. You need to use MiniTab to answer the questions and then paste your graphs and tables into a Word document for proper presentation.
One caution about all labs: Unless it is required, do not return raw data sets as part of your results. Lab reports should be as concise as possible. Submit your labs using the Dropbox created for that week's assignments. Doc Sharing and Journal areas should not be used for any work. File Naming Convention Please name your file using the following convention: "lastname_firstinitial_week#lab" For example, if you are Albert Einstein and you are submitting your Week 2 Lab, the filename should be "einstein_a_week2lab".
Deadlines See Syllabus/"Due Dates for Assignments & Exams" for due date information. Everyone involved in this class is expected to turn in original work. Any deviation from this policy will result in the actions specified in DeVry’s Academic Integrity Policy. Course Schedule Week, TCOs, and Topics Readings and Class Preparation Activities and Assignments Week 1 TCOs 1, 2, 3 Introduction to Statistics; Data Collection and Data Concepts Chapter 1: Introduction to Statistics Chapter 2: Descriptive Statistics Homework - MyStatLab Graded Discussion Topic Week 2 TCOs 9,10 Correlation and Regression Chapter 9: Correlation and Regression Chapter 11: Nonparametric Tests: Section 11.4 Homework - MyStatLab Lab Graded Discussion Topic Week 3 TCO 4 Rules of Probability, Probability Analysis Chapter 3: Probability Chapter 4: Discrete Probability Distributions: Section 4.1 Homework - MyStatLab Quiz Graded Discussion Topic Week 4 TCOs 3, 4, 5 Discrete Data Probability Distributions Chapter 4: Discrete Probability Distributions: Sections 4.2 and 4.3 Homework - MyStatLab Graded Discussion Topic Lab Week 5 TCO 6 Normal Probability Distributions Chapter 5: Normal Probability Distributions: Sections 5.1 to 5.4 Homework - MyStatLab Quiz Graded Discussion Topic Week 6 TCO 7 Confidence Intervals Chapter 6: Confidence Intervals: Sections 6.1 to 6.3 Homework - MyStatLab Graded Discussion Topic Lab Week 7 TCOs 8, 11 Hypothesis Testing Chapter 7: Hypothesis Testing with One Sample: Sections 7.1 to 7.4 Homework - MyStatLab Quiz Graded Discussion Topic Week 8 All TCOs Final Exam Optional Readings There are useful PowerPoint presentations in Doc Sharing for your review.
Each slide contains notes written specifically for our textbook by a MATH221 instructor. Thus, you will probably find the presentation very helpful! When you view the PowerPoints, make sure you are in the normal view so that you can read the notes below each slide. Due Dates for Assignments & Exams Unless otherwise specified, the following applies. · Access to most weeks begins on Sunday at 12:01 a.m. mountain time (MT). · All assignments are to be submitted on or before Sunday at the end of the specified week that they are due, by 11:59 p.m. (MT). · All quizzes and exams are to be completed on or before Sunday at the end of the specified week that they open, by 11:59 p.m. (MT). Week 8 opens at 12:01 a.m. (MT) on Sunday of the eighth week.
Any assignments or exams must be completed by 11:59 p.m. (MT) Saturday of the eighth week. Assignment Values and Letter Grades The maximum score in this class is 1,000 points. The categories, which contribute to your final grade, are weighted as follows. Assignment Points Weighting Discussions (Weeks 1 - 7; worth 20 pts. each) % Labs (Weeks 2, 4, 6; worth 50 pts. each) % Homework - MyStatLab (Weeks 1 - 7; worth 40 pts./week) % Quizzes (Weeks 3, 5, 7; 60 pts. each) % Final Exam % Total Points 1,% All of your course requirements are graded using points. At the end of the course, the points are converted to a letter grade using the scale in the table below.
Letter Grade Points Percentage A 900 – 1,% to 100% B 800 – % to 89% C 700 – % to 79% D 600 – % to 69% F 599 and below Below 60% Late Assignment Policy Undergraduate Attendance Policy Discussion Requirements In the Discussion areas of the course, you, as a student, can interact with your instructor and classmates to explore questions and comments related to the content of this course. Discussions will always close Sunday, 11:59 p.m. Mountain Time (MT). A successful student in online education is one who takes an active role in the learning process. You are, therefore, encouraged to participate in the discussion areas to enhance your learning experience throughout each week.
The discussions will be graded for 1. frequency – the number and regularity of your discussion comments, and 2. quality – the content of your contributions. Frequency – the number and regularity of your contributions. Students are expected to log in to the course and post (respond) in the discussion topics on a minimum of three separate days per week in each graded discussion, beginning no later than Wednesday. Quality – the content of your contributions. Examples of quality posts include · providing additional information to the discussion; · elaborating on previous comments from others; · presenting explanations of concepts or methods to help fellow students; · presenting reasons for or against a topic in a persuasive fashion; · sharing personal experiences that relate to the topic; and · providing a URL and an explanation for an area you researched on the Internet.
Full credit is awarded when both high quality and required frequency are met. For policy on discussions (and all other policies), please review the information contained in Policies under the Course Home section of your course. Plagiarism and Undergraduate Citations Frequently Asked Questions Student Disability Services What should I do if I have a disability that requires accommodation? DeVry University and Keller Graduate School of Management are committed to providing reasonable accommodations for eligible students with documented disabilities as defined by state and federal laws relating to the Americans with Disabilities Act (ADA). Our intent is to ensure that every student who makes a request for accommodations under ADA is advised of the accommodation process as promptly as possible.
If you are a student with a verifiable documented disability, and you can provide medical documentation regarding this disability, then contact our Office of Student Disability Services at [email protected] or [email protected] for more information on how to receive ADA accommodations in your classes. You may also fax your request to . Special Attendance Tracking Attendance in online and blended courses is tracked and recorded based on participation in online academic events. For blended courses, attendance may also be demonstrated by participation in onsite class meetings. Online academic events include participation in threaded discussions, submission of an assignment and completion of a quiz or exam.
However, these events are monitored only if they occur within the eCollege platform. Students completing assignments, quizzes or exams in MyMathLab, MyStatLab or MyITLab are no longer within the eCollege platform and as such these activities are not tracked for attendance purposes. Note!
Paper for above instructions
Applying Statistical Concepts to Business Situations: An Analytical Approach
Introduction
Statistics is a fundamental tool in today's business environment, providing insights that facilitate decision-making. The topics covered in the course "Elementary Statistics: Picturing the World" by Larson & Farber (2011) offer a strong foundation in statistical principles, techniques, and applications relevant to various business scenarios. This paper aims to explore the core statistical concepts detailed within the course framework, particularly focusing on sampling methods, descriptive statistics, probability analysis, confidence intervals, hypothesis testing, and regression analysis.
Statistical Decision-Making and Sampling Methods
Sampling Methods
The significance of sampling in business analytics lies in its ability to infer conclusions about a larger population without the cost and time often associated with collecting data from the entire group. Various sampling techniques, including simple random sampling, stratified sampling, and cluster sampling, can influence the reliability of the results obtained. According to Larson and Farber (2011), an appropriate sampling technique depends on factors such as the population's size, its characteristics, and the desired level of precision.
For instance, in a survey seeking to understand customer satisfaction across different demographics, a stratified sampling approach would ensure representation from various demographic groups (Israel, 2013). Calculating an ideal sample size is vital to achieving results that are both significant and practical. Utilizing the formula for sample size determination, which considers population size, confidence level, and margin of error, enables businesses to optimize their data collection processes (Yamane, 1967).
Descriptive Statistics: Central Tendency and Variability
Descriptive statistics serve to summarize and describe the characteristics of a dataset clearly. The course emphasizes the importance of measures such as mean, median, mode (central tendency), and range, variance, and standard deviation (variability).
1. Measures of Central Tendency:
- The mean provides a measure of average performance, while the median and mode offer valuable insights into the distribution's skewness or prevalence of certain values (Newman, 2014).
2. Measures of Variability:
- Standard deviation and variance inform about the dispersion of data points around the mean, critical for understanding consistency in sales performance, for instance. A higher standard deviation indicates a wider spread of data points (Gravetter & Wallnau, 2017).
Using graphical representations such as histograms allows businesses to visualize data distributions, making it easier to communicate findings to stakeholders (Cleveland, 1993).
Probability and Decision Making
Probability Concepts
Probability theory is essential in assessing the uncertainty associated with business decisions. The two primary types include discrete and continuous probability distributions. For instance, in inventory management, a discrete distribution could predict the likelihood of stocking a certain number of units based on historical sales data (Baan, 2013).
A calculated expected monetary value (EMV) can guide decision-making under uncertainty. This technique involves assigning probabilities to potential outcomes and calculating a weighted average of the outcomes, which helps in evaluating the risk versus reward (Hanke & Wichern, 2009).
Confidence Intervals and Hypothesis Testing
Confidence Intervals
A confidence interval offers a range of values that likely contain the population parameter, calculated using sample statistics. This statistical technique allows businesses to quantify the uncertainty associated with estimates such as average sales or mean production time (Wackerly, Mendenhall, & Beaver, 2008). For example, a confidence interval constructed for mean customer satisfaction ratings could guide strategy changes aimed at service improvement.
Hypothesis Testing
Hypothesis testing is a methodological approach that assists in validating business decisions through statistical evidence. By setting null and alternative hypotheses, businesses can use various tests (e.g., t-test, ANOVA) to assess whether observed data fall significantly outside the expected results (Siegel & Castellan, 1988). Hypothesis tests are crucial for evaluating promotional strategies or operational changes.
Regression Analysis
Linear Regression
Regression analysis, particularly linear regression, is a powerful tool for understanding the relationships between variables. Businesses can model the impact of independent variables (e.g., marketing spend) on a dependent variable (e.g., sales revenue), offering insights into potential return on investment (Montgomery, Peck, & Vining, 2012).
A well-fitted regression model can inform decisions on where to allocate resources effectively, as indicated by the coefficient of determination (R²), which measures the proportion of variance in the dependent variable explained by the independent variable (Keller & Warrack, 2014).
Conclusion
The application of statistical tools and concepts is essential for making informed decisions in business environments. Properly understanding sampling methods, descriptive statistics, probability analysis, confidence intervals, hypothesis testing, and regression analysis empowers organizations to base their strategies on solid evidence rather than intuition. This analytical approach, as highlighted throughout Larson and Farber's textbook, is critical in navigating the complexities and uncertainties inherent in today's dynamic business landscape.
References
1. Baan, C. (2013). The Balancing of Supply and Demand in Inventory Management. Journal of Operations Management, 31(3), 104-118.
2. Cleveland, W. S. (1993). Visualizing Data. Hobart Press.
3. Gravetter, F. J., & Wallnau, L. B. (2017). Statistics for The Behavioral Sciences (10th ed.). Cengage Learning.
4. Hanke, J. E., & Wichern, D. W. (2009). Business Forecasting (9th ed.). Prentice Hall.
5. Israel, G. D. (2013). Sampling the Easy Way. Florida Cooperative Extension Service, Institute of Food and Agricultural Sciences.
6. Keller, G., & Warrack, B. (2014). Statistics (7th ed.). Cengage Learning.
7. Montgomery, D. C., Peck, E. A., & Vining, G. G. (2012). Introduction to Linear Regression Analysis (5th ed.). Wiley.
8. Newman, S. (2014). Statistical Analysis: A Practical Guide for Researchers. Sage Publications.
9. Siegel, S., & Castellan, N. J. (1988). Nonparametric Statistics for the Behavioral Sciences (2nd ed.). McGraw-Hill.
10. Wackerly, D. D., Mendenhall, W., & Beaver, R. G. (2008). Mathematical Statistics with Applications (7th ed.). Thomson Brooks/Cole.
This outline serves as a structured walkthrough demonstrating how systematic applications of statistical methods facilitate robust business decision-making.