tailieunhanh - Lecture Statistical techniques in business and economics - Chapter 13: Linear regression and correlation

Chapter 13 - Linear regression and correlation, after studying this chapter you will be able to: Identify a relationship between variables on a scatter diagram, measure and interpret a degree of relationship by a coefficient of correlation, conduct a test of hypothesis about the coefficient of correlation in a population,.and other contents. | Chapter 13 Linear Regression and Correlation When you have completed this chapter, you will be able to: Chapter Goals Identify a relationship between variables on a scatter diagram Measure and interpret a degree of relationship by a coefficient of correlation Conduct a test of hypothesis about the coefficient of correlation in a population and. 1. 2. 3. 4. 13 13 - Identify the roles of dependent and independent variables, the concept of regression, and its distinction from the concept of correlation. Chapter Goals Conduct a test of hypothesis for a regression model and each coefficient of regression. 6. 7. 8. 13 Conduct analysis of variance and calculate coefficient of determination. Estimate confidence and prediction intervals 5. 13 - Measure and interpret the strength of relationship between two variables through a regression line and the technique of least squares. Terminology is a chart that portrays the relationship between the two variables. Scatter Diagram . | Chapter 13 Linear Regression and Correlation When you have completed this chapter, you will be able to: Chapter Goals Identify a relationship between variables on a scatter diagram Measure and interpret a degree of relationship by a coefficient of correlation Conduct a test of hypothesis about the coefficient of correlation in a population and. 1. 2. 3. 4. 13 13 - Identify the roles of dependent and independent variables, the concept of regression, and its distinction from the concept of correlation. Chapter Goals Conduct a test of hypothesis for a regression model and each coefficient of regression. 6. 7. 8. 13 Conduct analysis of variance and calculate coefficient of determination. Estimate confidence and prediction intervals 5. 13 - Measure and interpret the strength of relationship between two variables through a regression line and the technique of least squares. Terminology is a chart that portrays the relationship between the two variables. Scatter Diagram Correlation Analysis is a group of statistical techniques used to measure the strength of the association between two variables. Dependent Variable is the variable being predicted or estimated. provides the basis for estimation. It is the predictor variable. Independent Variable The Coefficient of Correlation r Is a measure of strength of the relationship between two variables It requires interval or ratio-scaled data It can range from to Values of or indicate perfect and strong correlation Values close to indicate weak correlation Negative values indicate an inverse relationship and positive values indicate a direct relationship 0 1 2 3 4 5 6 7 8 9 10 10 9 8 7 6 5 4 3 2 1 0 X Y Perfect Negative Correlation 0 1 2 3 4 5 6 7 8 9 10 10 9 8 7 6 5 4 3 2 1 0 X Y Perfect Positive Correlation 0 1 2 3 4 5 6 7 8 9 10 10 9 8 7 6 5 4 3 2 1 0 X Y Zero Correlation 0 1 2 3 4 5 6 7 8 9 10 10 9 8 7 6 5 4 3 2 1 0 X Y Example Strong Positive Correlation Chart 13-6 13 13 -

• Kinh tế học
• Statistical techniques
• Statistical techniques in business
• Statistical techniques in economics
• Descriptive statistics
• Linear regression
• Coefficient of correlation
• Statistical inference
• Independent samples
• Statistical process control
• Quality management
• Random observation
• Sampling methods
• Central limit theorem
• Confidence intervals
• Point estimator
• Confidence interval
• Hypothesis testing
• Alternative hypothesis
• Analysis of variance
• F distribution
• Multiple regression
• Multiple regression analysis
• Chi square applications
• Test of hypothesis
• Analysis of ranked data
• Kruskal Wallis test
• Index numbers
• Consumer price index
• Time series
• Linear trend equation
• Decision making
• Organize information
• The role of statistics
• Qualitative variable
• Describing data
• Frequency distribution
• Central tendency
• Standard deviation
• Ungrouped data
• Probability concepts
• Random experiment
• Discrete probability distributions
• Continuous random variables
• Decision theory
• Decision alternative
• Inferential statistics
• Frequency tables
• Numerical measures