TAILIEUCHUNG - Lecture Basic statistics for business and economics - Chapter 12: Analysis of variance

When you have completed this chapter, you will be able to: List the characteristics of the F distribution and locate values in an F table, perform a test of hypothesis to determine whether the variances of two populations are equal, describe the ANOVA approach for testing differences in sample means,. | Analysis of Variance Chapter 12 McGraw-Hill/Irwin Copyright © 2013 by The McGraw-Hill Companies, Inc. All rights reserved. We continue our discussion of hypothesis testing in this chapter. Recall that in chapters 10 and 11, we examined the general theory of hypothesis testing. In chapter 11, we learned the different procedures for testing one population parameter, and in chapter 12 we learned how to compare two population parameters. In this chapter, we will learn a procedure for comparing the means of three or more populations using the F distribution. Additionally, we will learn the other major uses of the F distribution. Learning Objectives LO 12-1 List the characteristics of the F distribution and locate values in an F table. LO 12-2 Perform a test of hypothesis to determine whether the variances of two populations are equal. LO 12-3 Describe the ANOVA approach for testing differences in sample means. LO 12-4 Organize data into appropriate ANOVA tables for analysis. LO 12-5 Conduct a test of hypothesis among three or more treatment means and describe the results. LO 12-6 Develop confidence intervals for the difference in treatment means and interpret the results. 12- The F Distribution Uses of the F distribution test whether two samples are from populations having equal variances. to compare several population means simultaneously. The simultaneous comparison of several population means is called analysis of variance (ANOVA). Assumption: In both of the uses above, the populations must follow a normal distribution, and the data must be at least interval-scale. Characteristics of the F distribution There is a “family” of F Distributions. A particular member of the family is determined by two parameters: the degrees of freedom in the numerator and the degrees of freedom in the denominator. The F distribution is continuous. F cannot be negative. The F distribution is positively skewed. It is asymptotic. As F the curve approaches the X-axis but never

• Kinh tế học
• Basic statistics
• Statistics for business
• Describing data
• Analysis of variance
• Equal variances
• Confidence interval
• Types of statistics
• Quantitative variables
• Ordinal level data
• Lecture Basic Statistics
• Bài giảng Thống kê cơ bản
• Introduction to Statistics
• Real limits
• Measuring variables
• Correlational studies
• Basic statistics for business
• Basic statistics for economics
• Graphic presentation
• Probability concepts
• Continuous probability distributions
• The central limit theorem
• Confidence intervals
• Two sample tests of hypothesis
• Linear regression
• Multiple regression
• Frequency tables
• Frequency distributions
• Numerical measures
• Sample mean
• Measures of dispersion
• Exploring data
• Dot plot
• Coefficient of skewness
• Joint probability
• Contingency table
• Discrete probability distributions
• Probability distribution
• Continuous random variable
• Uniform distribution
• Normal probability distribution
• Sampling methods
• Central limit theorem
• Probability sampling
• Point estimate
• One sample tests
• Hypothesis testing
• Test statistic
• Two sample tests
• Dependent variable
• Independent variable
• Multiple regression analysis
• Multiple linear regression
• Multiple determination
• Nonparametric methods
• Goodness of fit tests
• Contingency table analysis
• Basic business statistics
• Visualizing data
• Basic probability
• The normal distribution
• Other continuous distributions
• Statistical techniques
• Study statistics
• Inferential statistics
• The essentials of statistics
• Basic descriptive statistics
• Ratios and rates
• Central tendency
• The normal curve
• Financial risk management
• Statistics mathematics
• Risk management
• Financial risk
• Financial mathematics
• Some basic math
• Percentile ranks
• The binomial distribution
• descriptive statistics
• basic probability theory
• inductive statistics
• multivariate analysis
• firm understanding
• concise manner
• Conditional probability
• Bayes’ theorem