AS Statistics

By Mary Brace & Anthony Eccles, et al
June 2007
Pearson Education
ISBN: 9780340940525
512 pages, Illustrated, 7 1/2" x 9 3/4"
$77.50 Paper Original

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This accessible, comprehensive textbook is designed to support any student studying AS Statistics. This book covers all three AS modules: Z1, Z2 and Z3.

It has been designed especially for students with a non-mathematical background, but who nevertheless will need to understand some mathematical concepts when studying their other A levels. These students include those following Business Studies, Psychology, Geography and Biology courses.

This book is the only book supporting MEI AS Statistics and has all the benefits of being part of the MEI series: ­
Accessible both in design and content ­
Worked examples guide students into new
Topics and concepts within real world contexts (particularly important for these candidates)Activities, investigations and graded exercises ­
The quality assurance of MEI ­
Full support from the MEI network

In addition, there is an IT investigation at the end of each chapter.


Table of Contents:

Introduction
	Key to symbols in this book
Unit 1
	Exploring data
		Looking at the data
		Stem-and-leaf diagrams
		Categorical or qualitative data
		Numerical or quantitative data
		Measures of central tendancy
		Frequency distributions
		Grouped data
		Measures of spread
		Linear coding
	Data presentation and related measures of centre and spread
		Bar charts and vertical line charts
		Pie charts
		Histograms
		Measures of central tendancy and of spread using quartiles
		Cumulative frequency curves
	Probability
		Measuring probability
		Estimating probability
		Expectation
		The probability of either one event or another
		The probability of events from two trials
		Conditional probability
	Discrete random variables
		Discrete random variables
		Expectation and variance
	Further probability
		Factorials
		Permutations
		Combinations
		The bonomial coefficients, nCr
		Calculating probabilities in less simple cases
	The binomial distribution
		The binomial distribution
		The expectation of B(n, p)
		Using the binomial distribution
		Does the binomial distribution really work?
	Hypothesis testing using the binomial distribution
		Defining terms
		Hypothesis testing checklist
		Choosing the significance level
		Critical values and critical regions
		1-tailed and 2-tailed tests
		Asymmetrical cases
Unit 2
	The Poisson distribution
		Conditions for modelling data with a Poisson distribution
		The sum of two or more Poisson distributions
		The Poisson approximation to the binomial distribution
	The Normal distribution
		The key features of a Normal distribution
		The sum and difference of Normal variables
	The chi-squared test
		The X2 test for association
		Degrees of freedom
		Goodness of fit tests
	Using the Normal distribution to interpret sample data
		A hypothesis test for the mean using the Normal distribution
		Confidence intervals for a population mean
	Small samples and the t distribution
		The t distribution
		Confidence intervals from small samples
	The Wilcoxon signed rank test
		The Wilcoxon signed rank test for a single sample
Unit 3
	Sampling and experimental design
		Sampling
		Experiments and surveys
		Sampling methods
		Experimental design
		Design of experiments
	Hypothesis tests on paired samples
		Paired and unpaired experiments
		The paired-sample t test
		The Wilcoxon signed rank test for paired samples
	Hypothesis tests on unpaired samples
		Selecting the appropriate test for unpaired samples
		The Normal test for unpaired samples
		The t test for unpaired samples
		The Wilcoxon rank sum test
	Correlation
		Bivariate data
		Interpreting scatter diagrams
		Pearson's product moment correlation coefficient
		The meaning of a sample correlation coefficient
		Interpreting correlation
		Rank correlation
		Spearman's rank correlation coefficient
Appendices
		The derivation of the alternative form of the sum of squares, Sxx
		The binomial theorem
Answers
Index

 

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