TAILIEUCHUNG - Lecture Business statistics in practice (7/e): Chapter 2 - Bowerman, O'Connell, Murphree

Chapter 2 - Descriptive statistics: Tabular and graphical methods. After mastering the material in this chapter, you will be able to: Summarize qualitative data by using frequency distributions, bar charts, and pie charts; construct and interpret Pareto charts (Optional); summarize quantitative data by using frequency distributions, histograms, frequency polygons, and ogives;. | Chapter 2 Descriptive Statistics: Tabular and Graphical Methods Copyright © 2014 by The McGraw-Hill Companies, Inc. All rights reserved. McGraw-Hill/Irwin Descriptive Statistics Graphically Summarizing Qualitative Data Graphically Summarizing Quantitative Data Dot Plots Stem-and-Leaf Displays Crosstabulation Tables (Optional) Scatter Plots (Optional) Misleading Graphs and Charts (Optional) 2- Graphically Summarizing Qualitative Data With qualitative data, names identify the different categories This data can be summarized using a frequency distribution Frequency distribution: A table that summarizes the number of items in each of several non-overlapping classes LO2-1: Summarize qualitative data by using frequency distributions, bar charts, and pie charts. 2- Bar Charts and Pie Charts Bar chart: A vertical or horizontal rectangle represents the frequency for each category Height can be frequency, relative frequency, or percent .

• Quản trị kinh doanh
• Business Statistics
• Business statistics in practice
• Descriptive statistics
• Graphical methods
• Tabular methods
• Graphically summarizing qualitative data
• Lecture Business statistics
• Bài giảng Thống kê doanh nghiệp
• Descriptive statistics tabular
• Descriptive statistics graphical presentations
• Summarizing quantitative data
• Essentials of modern business statistics
• Modern business statistics
• Graphical presentations
• numerical measures
• Exploratory data analysis
• Interval estimation
• Hypothesis tests
• Simple linear regression
• Basic statistics
• Statistics for business
• Describing data
• Types of statistics
• Quantitative variables
• Ordinal level data
• Data sources
• Statistical inference
• Illustrate sampling
• Numerical methods
• Describing central tendency
• Measures of variation
• Sample spaces
• Elementary probability rules
• Compute conditional probabilities
• Discrete random variables
• Discrete probability distributions
• Binomial distribution
• Continuous random variables
• Continuous probability distributions
• Uniform distribution
• Sampling distributions
• Random sampling
• Stratified random
• Confidence intervals
• Sample size determination
• Hypothesis testing
• Alternative hypotheses
• Sampling distribution
• Equal variance
• Statistical inferences
• Population variances
• Experimental design
• Analysis of variance
• Randomized block design
• Chi square tests
• Chi square goodness of fit tests
• Multinomial experiment
• Simple linear regression analysis
• Simple linear regression model
• Model assumptions
• Multiple regression
• Least squares point estimate
• Multiple regression model
• Times series forecasting
• Index numbers
• Forecast error comparisons
• Statistical process control
• Causes of variation
• Control charts
• Nonparametric methods
• Hypothesis test
• Decision theory
• Utility theory
• Posterior probabilities