Quantitative Methods
Textbook: Statistical Techniques for Business and Economics (16e), by Lind, Marchal, and Wathan, McGraw-Hill, 2015. ISBN: 978-0078020520
Lind, Marchal, and Wathen official website
Go to this website for the PPT slides, tutorials, videos, datasets, quizzes, study guides, and other important chapter-by-chapter information.
TAMU Software Store
Z-tables and T-tables, F-tables
Chi-Square table
Binomial tables
Key Formulas
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Lind, Marchal, and Wathen official website
Go to this website for the PPT slides, tutorials, videos, datasets, quizzes, study guides, and other important chapter-by-chapter information.
TAMU Software Store
Z-tables and T-tables, F-tables
Chi-Square table
Binomial tables
Key Formulas
Join the Slack Team Page
CHAPTER MATERIAL
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Chapter 11: Two-Sample Test of Hypothesis
When you have completed this chapter, you will be able to:
LO11-1 Test a hypothesis that two independent population means are equal, assuming that the population standard deviations are known and equal.
LO11-2 Test a hypothesis that two independent population means are equal, with unknown population standard deviations.
LO11-3 Test a hypothesis about the mean population difference between paired or dependent observations.
LO11-4 Explain the difference between dependent and independent samples.
LO11-1 Test a hypothesis that two independent population means are equal, assuming that the population standard deviations are known and equal.
LO11-2 Test a hypothesis that two independent population means are equal, with unknown population standard deviations.
LO11-3 Test a hypothesis about the mean population difference between paired or dependent observations.
LO11-4 Explain the difference between dependent and independent samples.
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Chapter 12: Analysis of Variance
When you have completed this chapter, you will be able to:
LO12-1 Apply the F distribution to test a hypothesis that two population variances are equal.
LO12-2 Use ANOVA to test a hypothesis that three or more population means are equal.
LO12-3 Use confidence intervals to test and interpret differences between pairs of population means.
LO12-4 Use a blocking variable in a two-way ANOVA to test a hypothesis that three or more population means are equal.
LO12-5 Perform a two-way ANOVA with interaction and describe the results
LO12-1 Apply the F distribution to test a hypothesis that two population variances are equal.
LO12-2 Use ANOVA to test a hypothesis that three or more population means are equal.
LO12-3 Use confidence intervals to test and interpret differences between pairs of population means.
LO12-4 Use a blocking variable in a two-way ANOVA to test a hypothesis that three or more population means are equal.
LO12-5 Perform a two-way ANOVA with interaction and describe the results
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Chapter 13: Correlation and Linear Regression
When you have completed this chapter, you will be able to:
LO13-1 Explain the purpose of correlation analysis.
LO13-2 Calculate a correlation coefficient to test and interpret the relationship between two variables.
LO13-3 Apply regression analysis to estimate the linear relationship between two variables.
LO13-4 Evaluate the significance of the slope of the regression equation.
LO13-5 Evaluate a regression equation’s ability to predict using the standard estimate of the error and the coefficient of determination.
LO13-6 Calculate and interpret confidence and prediction intervals.
LO13-7 Use a log function to transform a nonlinear relationship.
LO13-1 Explain the purpose of correlation analysis.
LO13-2 Calculate a correlation coefficient to test and interpret the relationship between two variables.
LO13-3 Apply regression analysis to estimate the linear relationship between two variables.
LO13-4 Evaluate the significance of the slope of the regression equation.
LO13-5 Evaluate a regression equation’s ability to predict using the standard estimate of the error and the coefficient of determination.
LO13-6 Calculate and interpret confidence and prediction intervals.
LO13-7 Use a log function to transform a nonlinear relationship.
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Chapter 14: Multiple Regression Analysis
When you have completed this chapter, you will be able to:
LO14-1 Use multiple regression analysis to describe and interpret a relationship between several independent variables and a dependent variable.
LO14-2 Evaluate how well a multiple regression equation fits the data.
LO14-3 Test hypotheses about the relationships inferred by a multiple regression model.
LO14-4 Evaluate the assumptions of multiple regression.
LO14-5 Use and interpret a qualitative, dummy variable in multiple regression.
LO14-6 Include and interpret an interaction effect in multiple regression analysis.
LO14-7 Apply stepwise regression to develop a multiple regression model.
LO14-8 Apply multiple regression techniques to develop a linear model.
LO14-1 Use multiple regression analysis to describe and interpret a relationship between several independent variables and a dependent variable.
LO14-2 Evaluate how well a multiple regression equation fits the data.
LO14-3 Test hypotheses about the relationships inferred by a multiple regression model.
LO14-4 Evaluate the assumptions of multiple regression.
LO14-5 Use and interpret a qualitative, dummy variable in multiple regression.
LO14-6 Include and interpret an interaction effect in multiple regression analysis.
LO14-7 Apply stepwise regression to develop a multiple regression model.
LO14-8 Apply multiple regression techniques to develop a linear model.
Table 14-1 (Heating Cost Data)
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Chapter 15: Nonparametric Methods: Nominal Level Hypothesis Tests
When you have completed this chapter, you will be able to:
LO15-1 Test a hypothesis about a population proportion.
LO15-2 Test a hypothesis about two population proportions.
LO15-3 Test a hypothesis comparing an observed set of frequencies to an expected frequency distribution.
LO15-4 Explain the limitations of using the chi-square statistic in goodness-of-fit tests.
LO15-5 Test a hypothesis that an observed frequency distribution is normally distributed.
LO15-6 Perform a chi-square test for independence on a contingency table.
LO15-1 Test a hypothesis about a population proportion.
LO15-2 Test a hypothesis about two population proportions.
LO15-3 Test a hypothesis comparing an observed set of frequencies to an expected frequency distribution.
LO15-4 Explain the limitations of using the chi-square statistic in goodness-of-fit tests.
LO15-5 Test a hypothesis that an observed frequency distribution is normally distributed.
LO15-6 Perform a chi-square test for independence on a contingency table.
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Chapter 16: Nonparametric Methods: Analysis of Ordinal Data
When you have completed this chapter, you will be able to:
LO16-1 Use the sign test to compare two dependent populations.
LO16-2 Test a hypothesis about a median using the sign test.
LO16-3 Test a hypothesis of dependent populations using the Wilcoxon signed-rank test.
LO16-4 Test a hypothesis of independent populations using the Wilcoxon rank-sum test.
LO16-5 Test a hypothesis of several independent populations using the Kruskal-Wallis test.
LO16-6 Test and interpret a nonparametric hypothesis test of correlation.
LO16-1 Use the sign test to compare two dependent populations.
LO16-2 Test a hypothesis about a median using the sign test.
LO16-3 Test a hypothesis of dependent populations using the Wilcoxon signed-rank test.
LO16-4 Test a hypothesis of independent populations using the Wilcoxon rank-sum test.
LO16-5 Test a hypothesis of several independent populations using the Kruskal-Wallis test.
LO16-6 Test and interpret a nonparametric hypothesis test of correlation.
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Chapter 17: Index Numbers
When you have completed this chapter, you will be able to:
LO17-1 Compute and interpret a simple, unweighted index.
LO17-2 Compute and interpret an unweighted aggregate index.
LO17-3 Compute and interpret a weighted aggregate index.
LO17-4 List and describe special-purpose indexes.
LO17-5 Apply the Consumer Price Index.
LO17-1 Compute and interpret a simple, unweighted index.
LO17-2 Compute and interpret an unweighted aggregate index.
LO17-3 Compute and interpret a weighted aggregate index.
LO17-4 List and describe special-purpose indexes.
LO17-5 Apply the Consumer Price Index.
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Chapter 18: Times Series and Forecasting
When you have completed this chapter, you will be able to:
LO18-1 Define and describe the components of a time series.
LO18-2 Smooth a time series by computing a moving average.
LO18-3 Smooth a time series by computing a weighted moving average.
LO18-4 Use regression analysis to fit a linear trend line to a time series.
LO18-5 Use regression analysis to fit a nonlinear time series.
LO18-6 Compute and apply seasonal indexes to make seasonally adjusted forecasts.
LO18-7 Deseasonalize a time series using seasonal indexes.
LO18-8 Conduct a hypothesis test of autocorrelation.
LO18-1 Define and describe the components of a time series.
LO18-2 Smooth a time series by computing a moving average.
LO18-3 Smooth a time series by computing a weighted moving average.
LO18-4 Use regression analysis to fit a linear trend line to a time series.
LO18-5 Use regression analysis to fit a nonlinear time series.
LO18-6 Compute and apply seasonal indexes to make seasonally adjusted forecasts.
LO18-7 Deseasonalize a time series using seasonal indexes.
LO18-8 Conduct a hypothesis test of autocorrelation.
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Chapter 19: Statistical Process Control and Quality Management
When you have completed this chapter, you will be able to:
LO19-1 Explain the purpose of quality control in production and service operations.
LO19-2 Define the two sources of process variation and explain how they are used to monitor quality.
LO19-3 Explain the use of charts to investigate the sources of process variation.
LO19-4 Compute control limits for mean and range control charts for a variable measure of quality.
LO19-5 Evaluate control charts to determine if a process is out of control.
LO19-6 Compute control limits of control charts for an attribute measure of quality.
LO19-7 Explain the process of acceptance sampling.
LO19-1 Explain the purpose of quality control in production and service operations.
LO19-2 Define the two sources of process variation and explain how they are used to monitor quality.
LO19-3 Explain the use of charts to investigate the sources of process variation.
LO19-4 Compute control limits for mean and range control charts for a variable measure of quality.
LO19-5 Evaluate control charts to determine if a process is out of control.
LO19-6 Compute control limits of control charts for an attribute measure of quality.
LO19-7 Explain the process of acceptance sampling.
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Chapter 20: An Introduction to Decision Theory
When you have completed this chapter, you will be able to:
LO20-1 Identify and apply the three components of a decision.
LO20-2 Analyze a decision using expected monetary value.
LO20-3 Analyze a decision using opportunity loss.
LO20-4 Apply maximin, maximax, and minimax regret strategies to make a decision.
LO20-5 Compute and explain the expected value of perfect information.
LO20-6 Apply sensitivity analysis to evaluate a decision subject to uncertainty.
LO20-7 Use a decision tree to illustrate and analyze decision making under uncertainty.
LO20-1 Identify and apply the three components of a decision.
LO20-2 Analyze a decision using expected monetary value.
LO20-3 Analyze a decision using opportunity loss.
LO20-4 Apply maximin, maximax, and minimax regret strategies to make a decision.
LO20-5 Compute and explain the expected value of perfect information.
LO20-6 Apply sensitivity analysis to evaluate a decision subject to uncertainty.
LO20-7 Use a decision tree to illustrate and analyze decision making under uncertainty.
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