Basic Statistics With R: Reaching Decisions with Data

Contents_2022_Basic-Statistics-with-R.pdf
	Contents
Biography_2022_Basic-Statistics-with-R.pdf
	Biography
Preface_2022_Basic-Statistics-with-R.pdf
	Preface
Acknowledgments_2022_Basic-Statistics-with-R.pdf
	Acknowledgments
Chapter-1---What-is-statistics-and-why-is-it-impor_2022_Basic-Statistics-wit.pdf
	1 What is statistics and why is it important?
		1.1 Introduction
		1.2 So what is statistics?
			1.2.1 The process of statistics
			1.2.2 Hypothesis/questions
			1.2.3 Data collection
			1.2.4 Data description
			1.2.5 Statistical inference
			1.2.6 Theories/decisions
		1.3 Computation and statistics
Chapter-2---An-introduction-to-R_2022_Basic-Statistics-with-R.pdf
	2 An introduction to R
		2.1 Installation
		2.2 Classes of data
		2.3 Mathematical operations in R
		2.4 Variables
		2.5 Vectors
		2.6 Data frames
		2.7 Practice problems
		2.8 Conclusion
Chapter-3---Data-collection--methods-and-concern_2022_Basic-Statistics-with-.pdf
	3 Data collection: methods and concerns
		3.1 Introduction
		3.2 Components of data collection
		3.3 Observational studies
			3.3.1 Biases in survey sampling
			3.3.2 Practice problems
		3.4 Designed experiments
			3.4.1 Practice problems
		3.5 Observational studies and experiments: which to use?
			3.5.1 Practice problems
		3.6 Conclusion
Chapter-4---R-tutorial--subsetting-data--random-numbers-_2022_Basic-Statisti.pdf
	4 R tutorial: subsetting data, random numbers, and selecting a random sample
		4.1 Introduction
		4.2 Subsetting vectors
		4.3 Subsetting data frames
		4.4 Random numbers in R
		4.5 Select a random sample
		4.6 Getting help in R
		4.7 Practice problems
		4.8 Conclusion
Chapter-5---R-tutorial--libraries-and-loading-data_2022_Basic-Statistics-wit.pdf
	5 R tutorial: libraries and loading data into R
		5.1 Introduction
		5.2 Libraries in R
		5.3 Loading datasets stored in libraries
		5.4 Loading csv files into R
		5.5 Practice problems
		5.6 Conclusion
Chapter-6---Exploratory-data-analyses--describing-o_2022_Basic-Statistics-wi.pdf
	6 Exploratory data analyses: describing our data
		6.1 Introduction
		6.2 Parameters and statistics
		6.3 Parameters, statistics, and EDA for categorical variables
			6.3.1 Practice problems
		6.4 Parameters, statistics, and EDA for a single quantitative variable
			6.4.1 Statistics for the center of a variable
			6.4.2 Practice problems
			6.4.3 Statistics for the spread of a variable
			6.4.4 Practice problems
		6.5 Visual summaries for a single quantitative variables
		6.6 Identifying outliers
			6.6.1 Practice problems
		6.7 Exploring relationships between variables
		6.8 Exploring association between categorical predictor and quantitative response
			6.8.1 Practice problems
		6.9 Exploring association between two quantitative variables
			6.9.1 Practice problems
		6.10 Conclusion
Chapter-7---R-tutorial--EDA-in-R_2022_Basic-Statistics-with-R.pdf
	7 R tutorial: EDA in R
		7.1 Introduction
		7.2 Frequency and contingency tables in R
		7.3 Numerical exploratory analyses in R
			7.3.1 Summaries for the center of a variable
			7.3.2 Summaries for the spread of a variable
			7.3.3 Summaries for the association between two quantitative variables
		7.4 Missing data
		7.5 Practice problems
		7.6 Graphical exploratory analyses in R
			7.6.1 Scatterplots
			7.6.2 Histograms
		7.7 Boxplots
		7.8 Practice problems
		7.9 Conclusion
Chapter-8---An-incredibly-brief-introduction-to-pro_2022_Basic-Statistics-wi.pdf
	8 An incredibly brief introduction to probability
		8.1 Introduction
		8.2 Random phenomena, probability, and the Law of Large Numbers
		8.3 What is the role of probability in inference?
		8.4 Calculating probability and the axioms of probability
		8.5 Random variables and probability distributions
		8.6 The binomial distribution
		8.7 The normal distribution
		8.8 Practice problems
		8.9 Conclusion
Chapter-9---Sampling-distributions--or-why-exploratory-_2022_Basic-Statistic.pdf
	9 Sampling distributions, or why exploratory analyses are not enough
		9.1 Introduction
		9.2 Sampling distributions
		9.3 Properties of sampling distributions and the central limit theorem
		9.4 Practice problems
		9.5 Conclusion
Chapter-10---The-idea-behind-testing-hypotheses_2022_Basic-Statistics-with-R.pdf
	10 The idea behind testing hypotheses
		10.1 Introduction
		10.2 A lady tasting tea
		10.3 Hypothesis testing
			10.3.1 What are we testing?
			10.3.2 How rare is our data?
			10.3.3 What is our level of doubt?
		10.4 Practice problems
		10.5 Conclusion
Chapter-11---Making-hypothesis-testing-work-with-the-c_2022_Basic-Statistics.pdf
	11 Making hypothesis testing work with the central limit theorem
		11.1 Introduction
		11.2 Recap of the normal distribution
		11.3 Getting probabilities from the normal distributions
			11.3.1 Practice problems
		11.4 Connecting data to p-values
			11.4.1 Practice problems
		11.5 Conclusion
Chapter-12---The-idea-of-interval-estimates_2022_Basic-Statistics-with-R.pdf
	12 The idea of interval estimates
		12.1 Introduction
		12.2 Point and interval estimates
		12.3 When intervals are ``right''
		12.4 Confidence intervals
		12.5 Creating confidence intervals
		12.6 Interpreting confidence intervals
		12.7 Practice problems
		12.8 Conclusion
Chapter-13---Hypothesis-tests-for-a-single-parame_2022_Basic-Statistics-with.pdf
	13 Hypothesis tests for a single parameter
		13.1 Introduction
		13.2 One-sample test for proportions
			13.2.1 State hypotheses
			13.2.2 Set significance level
			13.2.3 Collect and summarize data
			13.2.4 Calculate test statistic
			13.2.5 Calculate p-values
			13.2.6 Conclude
			13.2.7 Practice problems
		13.3 One-sample t-test for means
			13.3.1 State hypotheses
			13.3.2 Set significance level
			13.3.3 Collect and summarize data
			13.3.4 Calculate test statistic
			13.3.5 Calculate p-values
			13.3.6 A brief interlude: the t distribution
			Back to p-values
			13.3.7 Conclude
			13.3.8 Practice problems
		13.4 Conclusion
Chapter-14---Confidence-intervals-for-a-single-par_2022_Basic-Statistics-wit.pdf
	14 Confidence intervals for a single parameter
		14.1 Introduction
		14.2 Confidence interval for p
			14.2.1 Practice problems
		14.3 Confidence interval for μ
			14.3.1 Practice problems
		14.4 Other uses of confidence intervals
			14.4.1 Confidence intervals for p and sample size calculations
			14.4.2 Practice problems
			14.4.3 Confidence intervals for μ and hypothesis testing
			14.4.4 Practice problems
		14.5 Conclusion
Chapter-15---Hypothesis-tests-for-two-parameters_2022_Basic-Statistics-with-.pdf
	15 Hypothesis tests for two parameters
		15.1 Introduction
		15.2 Two-sample test for proportions
			15.2.1 State hypotheses
			15.2.2 Set significance level
			15.2.3 Collect and summarize data
			15.2.4 Calculate the test statistic
			15.2.5 Calculate p-values
			15.2.6 Conclude
			15.2.7 Practice problems
		15.3 Two-sample t-test for means
			15.3.1 State hypotheses
			15.3.2 Set significance level
			15.3.3 Collect and summarize data
			15.3.4 Calculate the test statistic
			15.3.5 Calculate p-values
			15.3.6 Conclusion
			15.3.7 Practice problems
		15.4 Paired t-test for means
			15.4.1 State hypotheses
			15.4.2 Set significance level
			15.4.3 Collect and summarize data
			15.4.4 Calculate the test statistic
			15.4.5 Calculating p-values
			15.4.6 Conclude
			15.4.7 Practice problems
		15.5 Conclusion
Chapter-16---Confidence-intervals-for-two-paramet_2022_Basic-Statistics-with.pdf
	16 Confidence intervals for two parameters
		16.1 Introduction
		16.2 Confidence interval for p1-p2
			16.2.1 Practice problems
		16.3 Confidence interval for μ1-μ2
			16.3.1 Equal variances
			16.3.2 Unequal variances
			16.3.3 Interpretation and example
			16.3.4 Practice problems
		16.4 Confidence intervals for μD
			16.4.1 Practice problems
		16.5 Confidence intervals for μ1-μ2, μD, and hypothesis testing
			16.5.1 Practice problems
		16.6 Conclusion
Chapter-17---R-tutorial--statistical-inference-in_2022_Basic-Statistics-with.pdf
	17 R tutorial: statistical inference in R
		17.1 Introduction
		17.2 Choosing the right test
		17.3 Inference for proportions
			17.3.1 Inference for a single proportion
			17.3.2 Inference for two proportions
			17.3.3 Practice problems
		17.4 Inference for means
			17.4.1 Inference for a single mean
			17.4.2 Inference for two means
			17.4.3 Paired inference for means
			17.4.4 Practice problems
		17.5 Conclusion
Chapter-18---Inference-for-two-quantitative-varia_2022_Basic-Statistics-with.pdf
	18 Inference for two quantitative variables
		18.1 Introduction
		18.2 Test for correlations
			18.2.1 State hypotheses
			18.2.2 Set significance level
			18.2.3 Collect and summarize data
			18.2.4 Calculate the test statistic
			18.2.5 Calculate p-values
			18.2.6 Conclusion
			18.2.7 Practice problems
		18.3 Confidence intervals for correlations
		18.4 Test for correlations in R
		18.5 Confidence intervals for correlations
		18.6 Practice problems
		18.7 Conclusion
Chapter-19---Simple-linear-regression_2022_Basic-Statistics-with-R.pdf
	19 Simple linear regression
		19.1 Introduction
		19.2 Basic of lines
		19.3 The simple linear regression model
		19.4 Estimating the regression model
		19.5 Regression in R
		19.6 Practice problems
		19.7 Using regression to create predictions
		19.8 Practice problems
		19.9 The assumptions of regression
			19.9.1 Assumption 1: linearity
			19.9.2 Assumption 2: independence
			19.9.3 Assumption 3: zero mean
			19.9.4 Assumption 4: homoskedasticity
		19.10 Inference for regression
			19.10.1 State hypotheses
			19.10.2 Set significance level
			19.10.3 Collect and summarize data
			19.10.4 Calculate our test statistic
			19.10.5 Calculate p-values
			19.10.6 Conclusion
			19.10.7 Inference for regression in R
		19.11 How good is our regression?
		19.12 Practice problems
		19.13 Conclusion
Chapter-20---Statistics--the-world-beyond-this-bo_2022_Basic-Statistics-with.pdf
	20 Statistics: the world beyond this book
		20.1 Questions beyond the techniques of this book
		20.2 The answers statistics gives
		20.3 Where does this leave us?
Appendix-A---Solutions-to-practice-problems_2022_Basic-Statistics-with-R.pdf
	A Solutions to practice problems
		Chapter 2
		Chapter 3
		Chapter 4
		Chapter 5
		Chapter 6
		Chapter 7
		Chapter 8
		Chapter 9
		Chapter 10
		Chapter 11
		Chapter 12
		Chapter 13
		Chapter 14
		Chapter 15
		Chapter 16
		Chapter 17
		Chapter 18
		Chapter 19
Appendix-B---List-of-R-datasets_2022_Basic-Statistics-with-R.pdf
	B List of R datasets