TAILIEUCHUNG - Lecture Basic statistics for business and economics - Chapter 13: Correlation and linear regression

Chapter 13: Correlation and linear regression. When you have completed this chapter, you will be able to: Define the terms dependent variable and independent variable; calculate, test, and interpret the relationship between two variables using the correlation coefficient; apply regression analysis to estimate the linear relationship between two variables;. | Correlation and Linear Regression Chapter 13 Copyright © 2013 by The McGraw-Hill Companies, Inc. All rights reserved. McGraw-Hill/Irwin LEARNING OBJECTIVES LO 13-1 Define the terms dependent variable and independent variable. LO 13-2 Calculate, test, and interpret the relationship between two variables using the correlation coefficient. LO 13-3 Apply regression analysis to estimate the linear relationship between two variables LO 13-4 Interpret the regression analysis. LO 13-5 Evaluate the significance of the slope of the regression equation. LO 13-6 Evaluate a regression equation to predict the dependent variable. LO 13-7 Calculate and interpret the coefficient of determination. LO 13-8 Calculate and interpret confidence and prediction intervals. 13- In this chapter we’re going to learn how to use linear regression and perform correlation analysis in studying whether two variables are dependent or independent, measure the strength of their association, carry out tests to determine whether this association or correlation is significant, and use the regression model for estimating the response variable (Y) using prediction interval and confidence interval. Regression Analysis – Introduction Recall in Chapter 4, showing the relationship between two variables with a scatter diagram was introduced. In that case we showed that as the age of the buyer increased the amount spent for the vehicle also increased. In this chapter, we carry this idea further. Numerical measures to express the strength of relationship between two variables are developed. In addition, an equation is used to express the relationship between variables, allowing us to estimate one variable on the basis of another. EXAMPLES Is there a relationship between the amount Healthtex spends per month on advertising and its sales in the month? Can we base an estimate of the cost to heat a home in January on the number of square feet in the home? Is there a relationship between the miles per .

• Kinh tế học
• Basic statistics
• Statistics for business
• Describing data
• Linear regression
• Dependent variable
• Independent variable
• 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
• 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
• Confidence interval
• One sample tests
• Hypothesis testing
• Test statistic
• Equal variances
• Two sample tests
• Analysis of variance
• 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