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Basic Statistics and Data Analysis by Larry J. Kitchens (2002, Mixed Media)
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Ubicado en: Fiskdale, Massachusetts, Estados Unidos
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Entrega prevista entre el lun. 10 nov. y el lun. 17 nov. a 94104
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N.º de artículo de eBay:126845180820
Características del artículo
- Estado
- ISBN
- 9780534384654
Acerca de este producto
Product Identifiers
Publisher
Brooks/Cole
ISBN-10
053438465X
ISBN-13
9780534384654
eBay Product ID (ePID)
8038811697
Product Key Features
Number of Pages
656 Pages
Publication Name
Basic Statistics and Data Analysis
Language
English
Publication Year
2002
Subject
Probability & Statistics / General, Statistics
Type
Textbook
Subject Area
Mathematics, Social Science
Format
Mixed Lot
Dimensions
Item Height
1.2 in
Item Weight
47.2 Oz
Item Length
10.3 in
Item Width
7.8 in
Additional Product Features
Intended Audience
College Audience
LCCN
2002-103127
Dewey Edition
21
Illustrated
Yes
Dewey Decimal
519.5
Table Of Content
Preface. Introduction: An Invitation to Statistics. 1. DESCRIBING DATA WITH GRAPHS. Variables and Data. Types of Variables. Graphs for Categorical Data. Graphs for Quantitative Data. Relative Frequency Histograms. Key Concepts. About MINITAB?Introduction to MINITAB. Supplementary Exercises. Do It Yourself Exercises. Case Study: How Is Your Blood Pressure? 2. DESCRIBING DATA WITH NUMERICAL MEASURES. Describing a Set of Data with Numerical Measures. Measures of Center. Measures of Variability. On the Practical Significance of the Standard Deviation. A Check on the Calculation of s. Measures of Relative Standing. The Five-Number Summary and the Box Plot. Key Concepts and Formulas. About MINITAB?Numerical Descriptive Measures. Supplementary Exercises. Do It Yourself Exercises. Case Study: The Boys of Summer. 3. DESCRIBING BIVARIATE DATA. Bivariate Data. Graphs for Qualitative Variables. Scatterplots for Two Quantitative Variables. Numerical Measures for Quantitative Bivariate Data. Key Concepts. About MINITAB?Describing Bivariate Data. Supplementary Exercises. Do It Yourself Exercises. Case Study: Do You Think Your Dishes Are Really Clean? 4. PROBABILITY AND PROBABILITY DISTRIBUTIONS. The Role of Probability in Statistics. Events and the Sample Space. Calculating Probabilities Using Simple Events. Useful Counting Rules (Optional). Event Relations and Probability Rules. Conditional Probability, Independence, and the Multiplicative Rule. Bayes' Rule (Optional). Discrete Random Variables and their Probability Distributions. Key Concepts and Formulas. About MINITAB?Discrete Probability Distributions. Supplementary Exercises. Do It Yourself Exercises. Case Study: Probability and Decision Making in the Congo. 5. SEVERAL USEFUL DISCRETE DISTRIBUTIONS. Introduction. The Binomial Probability Distribution. The Poisson Probability Distribution. The Hypergeometric Probability Distribution. Key Concepts and Formulas. About MINITAB?Binomial and Poisson Probabilities. Supplementary Exercises. Do It Yourself Exercises. Case Study: A Mystery: Cancers Near a Reactor. 6. THE NORMAL PROBABILITY DISTRIBUTION. Probability Distributions for Continuous Random Variables. The Normal Probability Distribution. Tabulated Areas of the Normal Probability Distribution. The Normal Approximation to the Binomial Probability Distribution (Optional). Key Concepts and Formulas. About MINITAB?Normal Probabilities. Supplementary Exercises. Do It Yourself Exercises. Case Study: The Long and Short of It. 7. SAMPLING DISTRIBUTIONS. Introduction. Sampling Plans and Experimental Designs. Statistics and Sampling Distributions. The Central Limit Theorem. The Sampling Distribution of the Sample Mean. The Sampling Distribution of the Sample Proportion. A Sampling Application: Statistical Process Control (Optional). Key Concepts and Formulas. About MINITAB?The Central Limit Theorem at Work. Supplementary Exercises. Do It Yourself Exercises. Case Study: Sampling the Roulette at Monte Carlo. 8. LARGE-SAMPLE ESTIMATION. Where We've Been. Where We're Going?Statistical Inference. Types of Estimators. Point Estimation. Interval Estimation. Estimating the Difference between Two Population Means. Estimating the Difference between Two Binomial Proportions. One-Sided Confidence Bounds. Choosing the Sample Size. Key Concepts and Formulas. Supplementary Exercises. Do It Yourself Exercises. Case Study: How Reliable Is That Poll? 9. LARGE-SAMPLE TESTS OF HYPOTHESES. Testing Hypotheses about Population Parameters. A Statistical Test of Hypothesis. A Large-Sample Test about a Population Mean. A Large-Sample Test of Hypothesis for the Difference between Two Population Means. A Large-Sample Test of Hypothesis for a Binomial Proportion. A Large-Sample Test of Hypothesis for the Difference between Two Binomial Proportions. Some Comments on Testing Hypotheses. Key Concepts and Formulas. Supplementary Exercises. Do It Yourself Exercises. Case Study: An Aspirin a Day? 10. INFERENCE FROM S
Synopsis
With an emphasis on exploratory data analysis, this title teaches students to identify trends in their data that may help them ask the right questions. It develops students' statistical intuition and nurtures the development of a statistical way of thinking., With an emphasis on exploratory data analysis, BASIC STATISTICS AND DATA ANALYSIS teaches students to identify trends in their data that will help them ask the right questions. Rather than leading students through operations on data, this modern textbook stresses hands-on experience with more than 200 real data sets and approximately 1000 exercises in the book. This new text, a basic version of Larry Kitchens' groundbreaking text, EXPLORING STATISTICS, develops students' statistical intuition and nurtures the development of a statistical way of thinking. The author has shaped this text specifically for the elementary statistics course, leaving out the more advanced topics from his previous book. MINITAB? is the main statistical analysis software utilized in the text.
LC Classification Number
HA29.K574 2003
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