# Statistics 7th edition ( The Exploration and Analysis of Data )

## Statistics 7th edition ( The Exploration and Analysis of Data )

### Details of the book:

"STATISTICS: THE EXPLORATION AND ANALYSIS OF DATA", 7th Edition by Roxy Peck and Jay Devore is an introduction to statistics and data analysis where brilliant examples and real data are used all throughout the book. This textbook is traditional and modern, traditional in structure and modern in approach, Peck and Devore guides the students and readers through an intuition-based learning process and strong emphasis is given on communication and interpretation of statistical information. The use of simple notation and the substitution of words for the symbols in the book aid the students to build strong concepts and strengthen their comprehension. The activities and interactive applets provided in the book, "STATISTICS: THE EXPLORATION AND ANALYSIS OF DATA", 7th Edition makes it more perfect allowing the students to practice statistical problems.

The book contains the following:

• The importance of statistics and the data analysis process

• Variability and types of data

• Graphical representation of data

• At the end of each chapter, interpreting and communicating the results of Statistical Analyses, chapter reviews, extra problems and active examples are given.

• How data should be collected and sampling

• Different types of statistical studies-Observation and Experimentation

• Different types of graphical representations of both categorical and quantitative data.

• How data are described through numerical methods using central tendency, dispersion and data summarization using box-plots

• Chebyshev's Rule, the Empirical Rule, and z Scores

• How bivariate data is summarized using correlation and regression

• Linear, Non-linear and Logistic regression

• The concepts of probability include basic probability rules, decision making and estimating probabilities empirically and simulation.

• The distribution of population and normal distributions.

• How normality is checked and normalizing transformations

• Sampling variability and sampling distributions of a sample mean and proportion

• The method of estimation of a single sample includes point estimation and confidence interval

• Testing of hypothesis for a single sample

• The concepts of power, Type I and Type II errors etc.

• Inferences based on two populations or treatments

• How categorical data are analyzed using Chi-square tests, goodness of fit test, homogeneity test and independent test.

• Simple Linear Regression Model and checking model adequacy

• Inferences of a regression output, correlation coefficient etc.

• Multiple Linear Regression Model and inferences based on it.

• The method of one way and two way ANOVA and multiple comparisons.

• Non parametric inferences includes difference between two populations based on two independent and paired samples

• Non parametric or Distribution free ANOVA

TutorTeddy.com & Boston Predictive Analytics

[ Email your Statistics or Math problems to tutor@aafter.com (camera phone photos are OK) ]

Boston Office (Near MIT/Kendall 'T'):
Cambridge Innovation Center,