...BSHS 382 Week 5 Learning Team Statistics and Hypothesis Testing Presentation To Buy This material Click below link http://www.uoptutors.com/BSHS-382/BSHS-382-Week-5-Learning-Team-Statistics-and-Hypothesis-Testing-Presentation Prepare a 10- to 15-slide Microsoft® PowerPoint® presentation on statistics and hypothesis testing. This is a Microsoft® PowerPoint® presentation with speaker notes. Anorexia, as described on p. 383 of Statistics Enchiladas, as described on pp. 113 and 114 of Statistics FL Student Survey, as described on pp. 22 and 23 of Statistics Georgia Student Survey, as described on pp. 22, 23, and 151 of Statistics Olympic High Jump, as described on pp. 124, 125, and 128 of Statistics Introduction o Introduce the Learning Team members and the data set. o Briefly explain how the data was gathered and identify the study population. Descriptive Statistics o Define descriptive statistics and list the various descriptive measures. o Explain how descriptive statistical analysis increases understanding of the data. o Include an original graph created with StatCrunch that uses at least one descriptive statistical measure to illustrate the data set. Inferential Statistics o Define statistical inference and include and explain at least one original inferential statistical calculation. o Use StatCrunch to check the calculation and show the steps in your presentation. o Explain how inferential statistical analysis increases...
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... 3 Hypothesis Testing 5 3.1 Hypothesis 1 – Average Income level 5 Descriptive Statistics 5 Hypothesis of the test 5 Statistical Findings 6 Interpretation of results 6 3.2 Question 2: Satisfaction level between gender 7 Descriptive statistics 7 Hypothesis 7 Method used and nature of the test 7 Reporting of statistical analysis 8 Interpretation of results 8 3.3 Question 3: Difference between satisfaction levels across business divisions. 9 Descriptive Statistics 9 Hypothesis 9 Method used and the nature of the test 9 Reporting of Results 9 Interpretation of results 10 3.4 Question 4: Gender composition across divisions 11 Descriptive Statistics 11 Hypothesis 11 Method used 11 Reporting of Statistical analysis 11 Interpretation of results 12 3.5 Question 5: Years of service and overall satisfaction level 12 Null and alternate hypothesis 12 Method used 12 Nature of test used: 13 Reporting of Results 13 3.6 Question 6: Employment basis and their perception of their values. 14 Descriptive Statistics 14 Hypothesis 14 Method used and the nature of the test 14 Reporting of Results 15 Interpretation of results 15 3.7 Question 7: Difference between values employees placed on income and training opportunities 16 Descriptive statistics 16 Hypothesis 16 Method used and nature of the test 16 Reporting of statistical analysis 17 Interpretation of results 17 3.8 Question 8: Value on work social events and numbers of hours 18 Descriptive statistics 18 ...
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...One-Sample Tests of Hypothesis LEARNING OBJECTIVES 1 Define a hypothesis. 2 Explain the five-step hypothesis-testing procedure. 3 Define Type I and Type II errors. 4 Define the term test statistic and explain how it is used. 5 Distinguish between a one-tailed and a two-tailed hypothesis. 6 Conduct a test of hypothesis about a population mean. 7 Compute and interpret a p-value. 8 Conduct a test of hypothesis about a population proportion. 10-2 Define a hypothesis. Explain the five-step hypothesis-testing procedure. Hypothesis and Hypothesis Testing HYPOTHESIS A statement about the value of a population parameter developed for the purpose of testing. HYPOTHESIS TESTING A procedure based on sample evidence and probability theory to determine whether the hypothesis is a reasonable statement. 10-3 The Null and Alternate Hypotheses NULL HYPOTHESIS A statement about the value of a population parameter developed for the purpose of testing numerical evidence. ALTERNATE HYPOTHESIS A statement that is accepted if the sample data provide sufficient evidence that the null hypothesis is false. 10-4 Important Things to Remember about H0 and H1 H0: null hypothesis and H1: alternate hypothesis. H0 and H1 are mutually exclusive and collectively exhaustive. H0 is always presumed to be true. H1 has the burden of proof. A random sample (n) is used to “reject H0”. If we conclude “do not reject H0”, this does not necessarily ...
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...Introduction to Hypothesis Testing 8.1 8.2 8.3 8.4 8.5 CHAPTER 8 Inferential Statistics and Hypothesis Testing Four Steps to Hypothesis Testing Hypothesis Testing and Sampling Distributions Making a Decision: Types of Error Testing a Research Hypothesis: Examples Using the z Test Research in Focus: Directional Versus Nondirectional Tests Measuring the Size of an Effect: Cohen’s d Effect Size, Power, and Sample Size Additional Factors That Increase Power LEARNING OBJECTIVES After reading this chapter, you should be able to: 1 2 Identify the four steps of hypothesis testing. Define null hypothesis, alternative hypothesis, level of significance, test statistic, p value, and statistical significance. Define Type I error and Type II error, and identify the type of error that researchers control. Calculate the one-independent sample z test and interpret the results. Distinguish between a one-tailed and two-tailed test, and explain why a Type III error is possible only with one-tailed tests. Explain what effect size measures and compute a Cohen’s d for the one-independent sample z test. Define power and identify six factors that influence power. Summarize the results of a one-independent sample z test in American Psychological Association (APA) format. 8.6 3 4 5 8.7 8.8 8.9 8.10 SPSS in Focus: A Preview for Chapters 9 to 18 8.11 APA in Focus: Reporting the Test Statistic and Effect Size 6 7 8 2 PART III: PROBABILITY AND THE FOUNDATIONS OF INFERENTIAL STATISTICS 8.1 INFERENTIAL...
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...Assignment #1 MTH 233 Week 2 Learning Team Assignment: Learning Team Assignment #1 MTH 233 Week 3 Learning Team Assignment: Learning Team Assignment MTH 233 Week 4 Individual Assignment: Individual Assignment MTH 233 Week 5 Individual Assignment: Individual Assignment MTH 233 Week 5 Learning Team Assignment: Hypothesis Testing and Regression Analysis Paper only MTH 233 Learning Team Assignment: Hypothesis Testing and Regression Analysis Presentation ----------------------------------------------- MTH 233 Learning Team Assignment Hypothesis Testing and Regression Analysis Presentation For more classes visit www.snaptutorial.com Resources: University Library and the Internet Select a research issue, problem, or opportunity facing a Learning Team member’s organization to examine using hypothesis testing and a regression analysis on the collected data. Write a 1,050- to 1,750-word paper describing a new hypothesis test using a different statistic (e.g., large sample size, small sample size, means and/or proportions, one- and two-tailed tests) to perform on that data. Formulate a new hypothesis statement and perform the five-step hypothesis test on the data. Describe the results of the tests. Interpret the results of the regression analysis, state the limitations of the analysis, and describe the significance of the results to the organization. Be sure to attach the results of the regression analysis created in Microsoft® Excel to your paper. Present...
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...reflection for the last four weeks is as follows: The Steps in Testing a Research Hypothesis Hypothesis testing begins with a statement and assumption that determines the population of the mean, (Lind, 2011, p.288.). The five steps listed in Lind are as follows: 1. State null and alternate hypothesis 2. Select a level of significance 3. Identify the test statistic 4. Formulate a decision rule 5. Take a sample and arrive at decision However in McClave, 2011, pages 324 and 325 the steps for testing of a hypothesis are listed as “Elements of a Test of Hypothesis” and instead of five steps they list seven. The seven steps from McClave are listed as follows: 1. Null hypothesis: A theory about the specific values of one or more population parameters. The theory generally represents the status quo, which we adopt until it is proven false. The theory is always stated as Ho: parameter = value. 2. Alternative (research) hypothesis (Ha): A theory that contradicts the null hypothesis. The theory generally represents that which we will adopt when sufficient evidence exists to establish its truth. 3. Test statistic: A sample statistic used to decide whether to reject the null hypothesis. 4. Rejection region: The numerical values of the test statistic for which the null hypothesis will be rejected. The rejection region is chosen so that the probability α is that it will contain the test statistic when the null hypothesis is true, thereby leading to Type I error. The value of α is...
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...Nonparametric Hypothesis Testing RES/342 Nonparametric Hypothesis Testing During the course of the last three weeks, the team explored the hypothesis testing segment of statistics research. The first part of this assignment was the one sample hypothesis testing. The second was the two or more sample hypothesis testing, and finally in this third week, we will look at nonparametric hypothesis testing. This week’s project is a continuation of the previous projects and entails to build on the identical research question that we will frame a research hypothesis from the same provided data sets (Wage and Wage Earners) using ratio or interval numerical data; however, this week we will use a nonparametric hypothesis test to find our answer. In the next following paragraphs, the team will clearly affirm a hypothesis statement that will provide the base for our survey, perform a five-step hypothesis test on information concerning our choice and apply the concepts of nonparametric testing learned in this course, and describe how the results of our findings answer our research question. Finally, we will conclude this study with a brief summary that will examine the main points, the purpose, and conclusions of this final third week’s study on nonparametric testing. Perform the five-step hypothesis test on the data Nonparametric tests are statistical tests that analyze data that does not require assumptions about the distribution of shape of the population from which...
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...Time Series A time series is a sequence of observations which are ordered in time (or space). If observations are made on some phenomenon throughout time, it is most sensible to display the data in the order in which they arose, particularly since successive observations will probably be dependent. Time series are best displayed in a scatter plot. The series value X is plotted on the vertical axis and time t on the horizontal axis. Time is called the independent variable (in this case however, something over which you have little control). There are two kinds of time series data: Continuous, where we have an observation at every instant of time, e.g. lie detectors, electrocardiograms. We denote this using observation X at time t, X(t). Discrete, where we have an observation at (usually regularly) spaced intervals. We denote this as Xt. Examples Economics - weekly share prices, monthly profits Meteorology - daily rainfall, wind speed, temperature Sociology - crime figures (number of arrests, etc), employment figures COMPONENTS Trend Component We want to increase our understanding of a time series by picking out its main features. One of these main features is the trend component. Descriptive techniques may be extended to forecast (predict) future values. Trend is a long term movement in a time series. It is the underlying direction (an upward or downward tendency) and rate of change in a time series, when allowance has...
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...Hypothesis Testing and EViews p-values: Suppose that we want to test a null hypothesis about a single parameter using its estimated value (for example a mean or a regression coefficient). We can do so using a t-test. To begin, suppose that the parameter to be estimated is β. We must first specify a null hypothesis and an alternative hypothesis. 2 tail test: For a two tailed test, we want to test whether β is a particular value or not. We first set the value of β that we want to test. We’ll call this β0 to indicate that this will be the value of β under the null hypothesis. In a two tail test, the null and alternative hypotheses are: H0 : β = β 0 HA : β = β0 ˆ We proceed by estimating β. We denote the estimated value as β. This could for example be a sample mean estimate of the population mean, a least squared estimate of a regression coefficient, or a maximum likelihood estimate of a model coefficient, ˆ depending on the context. The estimate β is usually accompanied by a standard error ˆ to indicate how precisely it is estimated. We denote this standard error as se(β). This ˆ is a random variable with a sampling distribution. It will have reflects the fact the β different values in different samples. We can then form the following test statistic by computing the standardised statistic ˆ whereby we subtract the hypothesisized value β0 from the estimate β and divide by its standard error: t-stat = ˆ β − β0 ˆ se(β) ˆ Again, this test statistic is a random variable since it depends...
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...Hypothes9 9.1 Fundamentals of Hypothesis Testing: One-Sample Tests A Connection Between Confidence Interval Estimation and Hypothesis Testing Can You Ever Know the Population Standard Deviation? USING STATISTICS @ Oxford Cereals, Part II Fundamentals of Hypothesis-Testing Methodology The Null and Alternative Hypotheses The Critical Value of the Test Statistic Regions of Rejection and Nonrejection Risks in Decision Making Using Hypothesis Testing Hypothesis Testing Using the Critical Value Approach Hypothesis Testing Using the p-Value Approach 9.4 Z Test of Hypothesis for the Proportion The Critical Value Approach The p-Value Approach Potential HypothesisTesting Pitfalls and Ethical Issues 9.5 9.2 t Test of Hypothesis for the Mean (S Unknown) The Critical Value Approach The p-Value Approach Checking the Normality Assumption One-Tail Tests The Critical Value Approach The p-Value Approach 9.6 Online Topic: The Power of a Test USING STATISTICS @ Oxford Cereals, Part II Revisited CHAPTER 9 EXCEL GUIDE CHAPTER 9 MINITAB GUIDE 9.3 Learning Objectives In this chapter, you learn: • The basic principles of hypothesis testing • How to use hypothesis testing to test a mean or proportion • The assumptions of each hypothesis-testing procedure, how to evaluate them, and the consequences if they are seriously violated • How to avoid the pitfalls involved in hypothesis testing • Ethical issues involved in hypothesis testing U S I N G S TAT I S T I C S ...
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...Hypothesis Testing Statistical Method Karl Phillip R. Alcarde MBA University of Negros Occidental-Recoletos DEFINITION DEFINITION Hypothesis testing or significance testing is a method for testing a claim or hypothesis about a parameter in a population, using data measured in a sample. In this method, we test some hypothesis by determining the likelihood that a sample statistic could have been selected, if the hypothesis regarding the population parameter were true. Hypothesis testing or significance testing is a method for testing a claim or hypothesis about a parameter in a population, using data measured in a sample. In this method, we test some hypothesis by determining the likelihood that a sample statistic could have been selected, if the hypothesis regarding the population parameter were true. The method of hypothesis testing can be summarized in four steps. 1. To begin, we identify a hypothesis or claim that we feel should be tested. For example, we might want to test the claim that the mean number of hours that children in the United States watch TV is 3 hours. 2. We select a criterion upon which we decide that the claim being tested is true or not. For example, the claim is that children watch 3 hours of TV per week. Most samples we select should have a mean close to or equal to 3 hours if the claim we are testing is true. So at what point do we decide that the discrepancy between the sample mean and 3 is so big that the claim we...
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...Salaaka Reflection “The hypothesis guides us on the selection of a certain design, observation and methods of researching over others. If we could test the whole populations directly, we would not need to formulate hypothesis, conduct inferential statistics and make inferences for the population based on a sample. However, it is often impossible to test the whole population, and we need to make our observations based on a sample (University of Strathclyde Humanities & Social Studies, n.d.).” “Hypothesis testing is all about populations and using a sample based in which we make inferences about the population” (University of Strathclyde Humanities & Social Studies, n.d.). The basic logic is to prove or disprove the research question. There are five steps that consist of all the decisions a researchers needs to make in order to answer any research question. Steps in Testing a Research Hypothesis 1. Stating the Research Question. “This step makes the researcher not only define what is to be tested but what variable will be used in sample data collection” ("Five Steps of Hypothesis Testing", 2014). 2. Specify the Null and Alternative Hypothesis – According to the University of North Carolina (2014), "The second step is to state the research question in terms of a null hypothesis (H0) and a alternative hypothesis (HA). The null hypothesis is the population parameter, µ = $30,000 (H0: µ = $30,000). The alternative hypothesis is the population parameter...
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...the same on the exam as students in Math 163-02? 4. Is there any difference between the strengths of steel wire produced by the XY Company and Bob’s Wire Company? 5. A hospital spokesperson claims that the average daily room charge for a specific procedure is $622. Can we reject this claim? WHAT IS A HYPOTHESIS? Hypothesis: A statement about the value of a population parameter developed for the purpose of testing. Examples of hypotheses, or statements, made about a population parameter are: The mean monthly income from all sources for systems analysts is $3,625. Twenty percent of all juvenile offenders ultimately are caught and sentenced to prison. Hypothesis testing: A procedure, based on sample evidence and probability theory, used to determine whether the hypothesis is a reasonable statement and should not be rejected, or is unreasonable and should be rejected. lFollowing is a five-step procedure for testing a hypothesis. 5 STEPS IN THE HYPOTHESIS TESTING PROCEDURE 1. State the null hypothesis and the alternate hypothesis. Null Hypothesis – statement about the value of a population parameter. Alternate Hypothesis – statement that is accepted if evidence proves null hypothesis to be false. Tests of Hypotheses: z-test and...
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...Bahria University Bahria Institute of Management & Computer Sciences Karachi Campus Course Title: Statistical Inference Course Code: QTM 220 Credit Hours: Three Semester: 3rd Semester Prerequisite: QTM 160 Aims and Objectives: This main objective of this course is to provide wide application f the statistical tools in business management. It is also aims at to impart in-depth and rigorous knowledge to the business students to inculcate academic excellence in various fields of research and development, with special reference to business management. In addition it will provide necessary statistical knowledge and wide rage of ways to analyze data, which will improve the students statistical analytical and decision making skills. Session Lecture Outline Learning Objectives 01 Basic Probability and Discrete Probability Distributions Simple Probability To develop an understanding of basic probability concepts To introduce conditional probability To use Bayes’ Theorem to revise probabilities in light of new information To provide an understanding of the basic concepts of discrete probability distributions and their characteristics To develop the concept of mathematical expectation for a discrete random variable To introduce the covariance and illustrate its application in finance To present applications of the binomial distribution in business To present applications of the Poisson distribution in business 02 Counting Techniques 03 Continued...
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...The steps in testing a research hypothesis There are a total of five steps that are used in testing a hypothesis and they are: “(1) Making assumptions, (2) Stating the research and null hypotheses and selecting (setting) alpha, (3) Selecting the sampling distribution and specifying the test statistic, (4) Computing the test statistic, and (5) Making a decision and interpreting the results.” (Boston University Metropolitan College, n.d., Para. 1). When beginning the process of creating a hypothesis to test, the first thing that must be done is to make assumptions about the type of sampling method that would be used, the level of measurement for the variable, including the sample size. The second step is then to state the research and null hypotheses and selecting the alpha. “We always state research hypotheses in terms of population parameters because we want to use sample statistics to estimate population parameters.” (Boston University Metropolitan College, n.d., Para. 5). After the research has been stated, then the next step is to complete the null hypothesis, which will contradict the research hypothesis. The third step in testing a hypothesis is to select the sampling distribution and to specify the test statistic. The fourth step is to compute the test statistic following the specified formula to be able to test the statistic. The fifth and final step is to make a decision and to interpret the results. This simply means that we are looking over the results and deciding...
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