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Megastat 10.3

• New York, NY : McGraw-Hill/Irwin, [2014]
• Seventh edition.

Megastat 10.3 Download For Mac

• xxiii, 823 pages : illustrations ; 29 cm.

• HF1017 .B654 2014 QUARTO c. 1 | Virtual Shelf Browse
• HF1017.B654 2014 QUARTO c. 1 | Virtual Shelf Browse
  Checked out, Due: May 19 2021

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Megastat 10.3 Download

• Contributor: Bowerman, Bruce L.

• Leermiddelen (vorm)

• note: ch. 1 Introduction to Business Statistics
• 1.1. Data
• 1.2. Data Sources
• 1.3. Populations and Samples
• 1.4. Three Case Studies That Illustrate Sampling and Statistical Inference
• 1.5. Ratio, Interval, Ordinal, and Nominative Scales of Measurement (Optional)
• App 1.1 Getting Started with Excel
• App 1.2 Getting Started with MegaStat
• App 1.3 Getting Started with MINITAB
• ch. 2 Descriptive Statistics: Tabular and Graphical Methods
• 2.1. Graphically Summarizing Qualitative Data
• 2.2. Graphically Summarizing Quantitative Data
• 2.3. Dot Plots
• 2.4. Stem-and-Leaf Displays
• 2.5. Contingency Tables (Optional)
• 2.6. Scatter Plots (Optional)
• 2.7. Misleading Graphs and Charts (Optional)
• App 2.1 Tabular and Graphical Methods Using Excel
• App 2.2 Tabular and Graphical Methods Using MegaStat
• App 2.3 Tabular and Graphical Methods Using MINITAB
• ch. 3 Descriptive Statistics: Numerical Methods
• 3.1. Describing Central Tendency
• 3.2. Measures of Variation
• 3.3. Percentiles, Quartiles, and Box-and-Whiskers Displays
• 3.4. Covariance, Correlation, and the Least Squares Line (Optional)
• 3.5. Weighted Means and Grouped Data (Optional)
• 3.6. Geometric Mean (Optional)
• App 3.1 Numerical Descriptive Statistics Using Excel
• App 3.2 Numerical Descriptive Statistics Using MegaStat
• App 3.3 Numerical Descriptive Statistics Using MINITAB
• ch. 4 Probability
• 4.1. Probability and Sample Spaces
• 4.2. Probability and Events
• 4.3. Some Elementary Probability Rules
• 4.4. Conditional Probability and Independence
• 4.5. Bayes' Theorem (Optional)
• 4.6. Counting Rules (Optional)
• ch. 5 Discrete Random Variables
• 5.1. Two Types of Random Variables
• 5.2. Discrete Probability Distributions
• 5.3. Binomial Distribution
• 5.4. Poisson Distribution (Optional)
• 5.5. Hypergeometric Distribution (Optional)
• 5.6. Joint Distributions and the Covariance (Optional)
• App 5.1 Binomial, Poisson, and Hypergeometric Probabilities Using Excel
• App 5.2 Binomial, Poisson, and Hypergeometric Probabilities Using MegaStat
• App 5.3 Binomial, Poisson, and Hypergeometric Probabilities Using MINITAB
• ch. 6 Continuous Random Variables
• 6.1. Continuous Probability Distributions
• 6.2. Uniform Distribution
• 6.3. Normal Probability Distribution
• 6.4. Approximating the Binomial Distribution by Using the Normal Distribution (Optional)
• 6.5. Exponential Distribution (Optional)
• 6.6. Normal Probability Plot (Optional)
• App 6.1 Normal Distribution Using Excel
• App 6.2 Normal Distribution Using MegaStat
• App 6.3 Normal Distribution Using MINITAB
• ch. 7 Sampling and Sampling Distributions
• 7.1. Random Sampling
• 7.2. Sampling Distribution of the Sample Mean
• 7.3. Sampling Distribution of the Sample Proportion
• 7.4. Stratified Random, Cluster, and Systematic Sampling (Optional)
• 7.5. More about Surveys and Errors in Survey Sampling (Optional)
• 7.6. Derivation of the Mean and the Variance of the Sample Mean (Optional)
• App 7.1 Generating Random Numbers Using Excel
• App 7.2 Generating Random Numbers Using MegaStat
• App 7.3 Generating Random Numbers and Simulating Sampling Distributions Using MINITAB
• ch. 8 Confidence Intervals
• 8.1. z-Based Confidence Intervals for a Population Mean: σ Known
• 8.2. t-Based Confidence Intervals for a Population Mean: σ Unknown
• 8.3. Sample Size Determination
• 8.4. Confidence Intervals for a Population Proportion
• 8.5. Confidence Intervals for Parameters of Finite Populations (Optional)
• App 8.1 Confidence Intervals Using Excel
• App 8.2 Confidence Intervals Using MegaStat
• App 8.3 Confidence Intervals Using MINITAB
• ch. 9 Hypothesis Testing
• 9.1. Null and Alternative Hypotheses and Errors in Hypothesis Testing
• 9.2. z Tests about a Population Mean: σ Known
• 9.3. t Tests about a Population Mean: σ Unknown
• 9.4. z Tests about a Population Proportion
• 9.5. Type II Error Probabilities and Sample Size Determination (Optional)
• App 9.1 One-Sample Hypothesis Testing Using Excel
• App 9.2 One-Sample Hypothesis Testing Using MegaStat
• App 9.3 One-Sample Hypothesis Testing Using MINITAB
• ch. 10 Comparing Two Means and Two Proportions
• 10.1. Comparing Two Population Means by Using Independent Samples
• 10.2. Paired Difference Experiments
• 10.3. Comparing Two Population Proportions by Using Large, Independent Samples
• App 10.1 Two-Sample Hypothesis Testing Using Excel
• App 10.2 Two-Sample Hypothesis Testing Using MegaStat
• App 10.3 Two-Sample Hypothesis Testing Using MINITAB
• ch. 11 Statistical Inferences for Population Variances
• 11.1. Chi-Square Distribution
• 11.2. Statistical Inference for a Population Variance
• 11.3. F Distribution
• 11.4. Comparing Two Population Variances by Using Independent Samples
• App 11.1 Two-Sample Hypothesis Test for the Equality of Two Variances Using Excel
• App 11.2 One- and Two-Sample Hypothesis Tests for Variances Using MegaStat
• App 11.3 One- and Two-Sample Inferences for Variances Using MINITAB
• ch. 12 Experimental Design and Analysis of Variance
• 12.1. Basic Concepts of Experimental Design
• 12.2. One-Way Analysis of Variance
• 12.3. Randomized Block Design
• 12.4. Two-Way Analysis of Variance
• App 12.1 Experimental Design and Analysis of Variance Using Excel
• App 12.2 Experimental Design and Analysis of Variance Using MegaStat
• App 12.3 Experimental Design and Analysis of Variance Using MINITAB
• ch. 13 Chi-Square Tests
• 13.1. Chi-Square Goodness-of-Fit Tests
• 13.2. Chi-Square Test for Independence
• App 13.1 Chi-Square Tests Using Excel
• App 13.2 Chi-Square Tests Using MegaStat
• App 13.3 Chi-Square Tests Using MINITAB
• ch. 14 Simple Linear Regression Analysis
• 14.1. Simple Linear Regression Model and the Least Squares Point Estimates
• 14.2. Model Assumptions and the Standard Error
• 14.3. Testing the Significance of the Slope and y-Intercept
• 14.4. Confidence and Prediction Intervals
• 14.5. Simple Coefficients of Determination and Correlation
• 14.6. Testing the Significance of the Population Correlation Coefficient (Optional)
• 14.7. F-Test for the Model
• 14.8. QHIC Case: Developing An Advertising Strategy
• 14.9. Residual Analysis
• 14.10. Some Shortcut Formulas (Optional)
• App 14.1 Simple Linear Regression Analysis Using Excel
• App 14.2 Simple Linear Regression Analysis Using MegaStat
• App 14.3 Simple Linear Regression Analysis Using MINITAB
• ch. 15 Multiple Regression and Model Building
• 15.1. Multiple Regression Model and the Least Squares Point Estimates
• 15.2. Model Assumptions and the Standard Error
• 15.3. R2 and Adjusted R2
• 15.4. Overall F-Test
• 15.5. Testing the Significance of an Independent Variable
• 15.6. Confidence and Prediction Intervals
• 15.7. Sales Representative Case: Evaluating Employee Performance
• 15.8. Using Dummy Variables to Model Qualitative Independent Variables
• 15.9. Using Squared and Interaction Variables
• 15.10. Model Building and the Effects of Multicollinearity
• 15.11. Residual Analysis in Multiple Regression
• 15.12. Logistic Regression
• App 15.1 Multiple Regression Analysis Using Excel
• App 15.2 Multiple Regression Analysis Using MegaStat
• App 15.3 Multiple Regression Analysis Using MINITAB
• ch. 16 Time Series Forecasting and Index Numbers
• 16.1. Time Series' Components and Models
• 16.2. Time Series Regression
• 16.3. Multiplicative Decomposition
• 16.4. Simple Exponential Smoothing
• 16.5. Holt-Winters' Models
• 16.6. Brief Introduction to Box-Jenkins Models (Optional Advanced Section)
• 16.7. Forecast Error Comparisons
• 16.8. Index Numbers
• App 16.1 Time Series Analysis Using Excel
• App 16.2 Time Series Analysis Using MegaStat
• App 16.3 Time Series Analysis Using MINITAB
• ch. 17 Process Improvement Using Control Charts
• 17.1. Quality: Its Meaning and a Historical Perspective
• 17.2. Statistical Process Control and Causes of Process Variation
• 17.3. Sampling a Process, Rational Subgrouping, and Control Charts
• 17.4. x and R Charts
• 17.5. Comparison of a Process with Specifications: Capability Studies
• 17.6. Charts for Fraction Nonconforming
• 17.7. Cause-and-Effect and Defect Concentration Diagrams (Optional)
• App 17.1 Control Charts Using MegaStat
• App 17.2 Control Charts Using MINITAB
• ch. 18 Nonparametric Methods
• 18.1. Sign Test: A Hypothesis Test about the Median
• 18.2. Wilcoxon Rank Sum Test
• 18.3. Wilcoxon Signed Ranks Test
• 18.4. Comparing Several Populations Using the Kruskal-Wallis H Test
• 18.5. Spearman's Rank Correlation Coefficient
• App 18.1 Nonparametric Methods Using MegaStat
• App 18.2 Nonparametric Methods Using MINITAB
• ch. 19 Decision Theory
• 19.1. Introduction to Decision Theory
• 19.2. Decision Making Using Posterior Probabilities
• 19.3. Introduction to Utility Theory.

• Includes bibliographical references (pages 814-815) and index.

Megastat 10.3 Pro

• 9780073521497
• 0073521493
• 9781259060397
• 125906039X

Megastat 10.3 Update

• LCCN: 2012044956
• OCLC: 818985425
• OCLC: 818985425