- Ohio State University Libraries
- Research Guides
- STAT 1450
- Recommended Sources

Introduction to the Practice of Statistics

Mathematical Sciences Librarian

Science Education Specialist

- OSU Library CatalogSearch for books and other items available at OSU - includes ebooks
- OhioLINK CatalogSearch for books statewide.

- Electronic Book Center (OhioLINK) [Full Text] This link opens in a new windowElectronic Book Center included ebooks on all subjects, including many encyclopedias, handbooks, biographical collections, and guides.

The OSU Library Catalog has subject headings. If you had found a good book on your topic, examine the subject headings for that book below the location/call number box. You can click on these to see other items with that subject ot you can search subject directly as follows.

Examples:

"History" is a subdivision of a subject that can be added after any other term. Examples: Format: branch--history. Clickable examples:

For mathematics history in a country, region, use for format mathematics--country/region--history Examples:

Citation databases allow you to see for each article the items it cited and also the items that have cited it. If you find a great article, use these databases to move both back and forward in time from that article.

- Scopus This link opens in a new windowScopus is a citation database of peer-reviewed literature and quality web sources with smart tools to track analyze and visualize research. Tools to sort, refine and quickly identify results help researchers focus on the outcome of their work.
- Web of Science Core Collection This link opens in a new windowProvides access to citation indexes which can be searched individually or as one file.
- Arts & Humanities Citation Index indexes 1,100 of the world's leading arts and humanities journals, as well as covering individually selected, relevant items from over 6,800 major science and social science journals.
- Science Citation Index Expanded indexes 5,300 major journals across 164 scientific disciplines and contains searchable, full-length, English-language author abstracts for approximately 70 percent of the articles in the database.
- The Social Sciences Citation Index indexes 1,700 journals spanning 50 disciplines, as well as covering individually selected, relevant items from over 3,300 of the world's leading scientific and technical journals.
- Book Citation Indexes- Science and Social Sciences & Humanties indexes over 30,000 editorially selected books in the sciences, social sciences and humanities, with 10,000 new books added each year. It contains searchable, full-length, English-language author abstracts for approximately 60 per cent of the articles in the database.

- Computers and Applied Sciences Complete [Selected Articles in Full Text] This link opens in a new windowComputers & Applied Sciences Complete (CASC) covers the spectrum of the applied sciences, representing knowledge on traditional engineering challenges and providing material for research concerning the business and social implications of new technology. CASC provides indexing and abstracting for more than 1,300 academic journals, professional publications, and other reference sources. Full Text is also available for more than 500 periodicals. Subject areas include the many engineering disciplines, computer theory, and new technologies. Includes Computer Source - Consumer Edition.

- JSTOR [Selected Articles in Full Text] This link opens in a new windowJSTOR offers multidisciplinary and discipline-specific collections in the humanities, sciences and social sciences. The moving wall represents the time period between the last issue available in JSTOR and the most recently published issue of a journal. It is specified by publishers in their license agreements with JSTOR, and generally ranges from 3 and 5 years. In calculating the moving wall, the current, incomplete year is not counted.
- Academic Search Complete [Selected Articles in Full Text] This link opens in a new windowAcademic Search Complete is comprehensive scholarly, multi-disciplinary full-text database, with more than 5,300 full-text periodicals, including 4,400 peer-reviewed journals. In addition to full text, this database offers indexing and abstracts for more than 9,300 journals and a total of 10,900 publications including monographs, reports, conference proceedings, etc.
- Google Scholar This link opens in a new windowConnect Google Scholar to Find It! by going to Settings > Library Links. There, search for Ohio State, choose the Ohio State option, and save.

You'll see some important buttons while using the OSU Libraries resouces. Especially important are these 4:

Where: OSU Library Catalog.

What: Have an item sent to another location for pickup or recall an item checked out.

Where: OSU Library Catalog.

What: Check for access of an individual item via OhioLINK - such as an item checked out at OSU. Also repeats searches in the OHioLINK catalog to see additional options for your need.

Where: OhioLINK Catalog

What: Click to have an item delivered to OSU from an OhioLINK library.

Where: Library Databases

What: Check for online access to journal articles, conference papers, and more. Also gives interlibrary loan option if item is not available online.

Picturing Distributions with Graphs

- Summarizing Data : Lecture 1, Part 2
- Khan Academy: Thinking about shapes of distributions
- Khan Academy: Visualizing a binomial distribution
- Khan Academy: Visualizing a binomial distribution
- Khan Academy: Classifying shapes of distributions
- Khan Academy: Median, mean and skew from density curves
- Khan Academy: Example: Describing a distribution
- Khan Academy: Ways to represent data

Describing Distributions with Numbers

- Khan Academy: Introduction to sampling distributions

The Normal Distribution

- The normal distribution
- Finding probability using a normal distribution. Part 1
- Finding probability using a normal distribution. Part 2
- Finding probability using a normal distribution. Part 3
- Finding probability using a normal distribution. Part 4
- Finding probability using a normal distribution. Part 5
- Finding Z-values with a normal distribution. Part 1
- Finding Z-values with a normal distribution. Part 2
- Finding Z-values with a normal distribution. Part 3
- Finding z-values with a normal distribution. Part 4
- Properties of the normal distribution
- The area under the normal distribution
- The normal probability distribution
- The standard normal distribution
- Khan Academy: Introduction to the normal distribution
- Khan Academy: Normal distribution problems: z-score
- Khan Academy: Normal distribution problems: Qualitative sense of normal distributions
- Khan Academy: Normal distribution problems: Empirical rule
- Khan Academy: Standard normal distribution and the empirical

Scatterplots & Correlation

- Scatterplots
- Scatter Plots and Gym Training
- Correlation and causation : Tyler Vigen's spurious correlations
- Correlation
- An introduction to partial correlations
- Does correlation prove causation in predictive analytics?
- Correlation
- Correlation and Causation : Illustrating the Difference
- Khan Academy: Constructing a scatter plot
- Khan Academy: Studying, shoe size, and test scores scatter plots
- Khan Academy: Constructing scatter plot exercise example
- Khan Academy: People smoking less over time scatter plot
- Khan Academy: Calculating correlation coefficient r
- Khan Academy: Correlation and causality
- Khan Academy: Example: Correlation coefficient intuition

Regression

- Call center forecasting : linear regression models
- An introduction to correlation & regression
- An introduction to regression diagnostics
- Correlation and regression - Pearson
- Correlation and regression - Spearman
- Correlation & simple regression
- Introduction to regression model
- Logistic regression
- Logistic regression
- Summary of regression models
- Use of regression models
- What is robust regression?
- Inference for Regression
- Khan Academy: Regression line example
- Khan Academy: R-squared or coefficient of determination
- Khan Academy: Covariance and the regression line
- Khan Academy: Squared error of regression line
- Khan Academy: Interpreting y-intercept in regression model
- Khan Academy: Introduction to inference about slope in linear regression
- Khan Academy: Calculating t statistic for slope of regression line
- Khan Academy: Confidence interval for the slope of a regression line
- Khan Academy: Calculating the equation of a regression line
- Khan Academy: Second regression example
- Khan Academy: Interpreting slope of regression line
- Khan Academy:Calculating R-squared
- Khan Academy:Example estimating from regression line
- Khan Academy: Fitting a line to data
- Khan Academy Worked example of linear regression using transformed data
- Khan Academy: Estimating the line of best fit exercise

Two-Way Tables

- Two-Way Tables
- Inference for Two-Way Tables
- Khan Academy: Two-way frequency tables and Venn diagrams
- Khan Academy: Two-way relative frequency tables
- Khan Academy: Interpreting two-way tables
- Khan Academy: Data in two way frequency tables
- Khan Academy: Filling out frequency table for independent events

Producing Data: Sampling

- An introduction to sampling
- Random sampling
- Sampling
- Sampling distributions
- Census and Sampling
- Sampling Distributions
- Sampling, Surveying, and Data Analysis
- Sampling distributions and large samples
- Khan Academy: Introduction to sampling distributions
- Khan Academy: Techniques for random sampling and avoiding bias
- Khan Academy: Identifying a sample and population
- Khan Academy: Reasonable samples
- Khan Academy: Techniques for generating a simple random sample

Producing Data: Experiments

- Behind the Statistics
- Quality and validity in animal research
- A/B testing, a data science perspective : an introduction to data and statistics for improved U/X
- Understanding scientific measurement
- Organizing quantitative data
- Khan Academy: Introduction to experiment design
- Khan Academy: Data to justify experimental claims examples
- Khan Academy: Worked example identifying observational study
- Khan Academy: Experimental probability
- Khan Academy: Statistical significance of experiment
- Khan Academy: Types of statistical studies
- Khan Academy: Matched pairs experiment design
- Khan Academy: Worked example identifying experiment

Introducing Probability

- Introduction to Probability
- Probability - introduction
- Introduction to probability
- Probability
- Probability
- Probability
- Conditional probability
- Probability trees
- Data Analysis and Probability
- Probability Models
- Khan Academy: Probability explained
- Khan Academy: Probability (part 2)
- Khan Academy: Probability (part 3)
- Khan Academy: Probability (part 4)
- Khan Academy: Probability (part 5)
- Khan Academy: Probability (part 6)
- Khan Academy: Probability (part 7)
- Khan Academy: Probability (part 8)
- Khan Academy: Combinations
- Khan Academy: Permutations
- Khan Academy: Probability using combinations
- Khan Academy: Probability and combinations (part 2)
- Khan Academy: Conditional probability and combinations
- Khan Academy: Birthday probability problem
- Khan Academy: Free throwing probability
- Khan Academy: Three pointer vs free throwing probability
- Khan Academy: Mega millions jackpot probability
- Khan Academy: Probability with playing cards and Venn diagrams
- Khan Academy: Coin flipping probability
- Khan Academy: Exactly three heads in five flips
- Khan Academy: Getting exactly two heads (combinatorics)
- Khan Academy: Dependent probability example
- Khan Academy: Finding probability example 2
- Khan Academy: Compound probability of independent events
- Khan Academy: Probability without equally likely events
- Khan Academy: Frequency stability property short film
- Khan Academy: Introduction to Random Variables
- Khan Academy: Law of large numbers

General Rules of Probability

- Khan Academy: Addition rule for probability

- Poisson probability distribution and the urn model
- Khan Academy: Introduction to sampling distributions
- Khan Academy: Sampling distribution of the sample mean
- Khan Academy: Sampling distribution example problem
- Khan Academy: Sampling distribution of sample proportion part 1
- Khan Academy: Sampling distribution of sample proportion part 2
- Khan Academy: Probability of sample proportions example
- Khan Academy: Sampling distribution of the sample mean
- Khan Academy: Sampling distribution of the sample mean 2
- Khan Academy: Central limit theorem
- Khan Academy: Standard error of the mean
- Khan Academy: Normal conditions for sampling distributions of sample proportions
- Khan Academy: Sample statistic bias worked example

- Confidence Intervals
- Small Sample Inference for One Mean
- Confidence intervals for population means. Part 1
- Confidence intervals for population means. Part 2
- Khan Academy: Confidence interval example | Inferential statistics | Probability and Statistics | Khan Academy
- Khan Academy: Small sample size confidence intervals
- Khan Academy: Confidence intervals for the difference between two proportions
- Khan Academy: Confidence interval of difference of means
- Khan Academy: Confidence interval for the slope of a regression line
- Khan Academy: Example constructing a t interval for a mean
- Khan Academy: Conditions for valid confidence intervals
- Khan Academy: Sample size for a given margin of error for a mean
- Khan Academy: Conditions for confidence intervals worked examples
- Khan Academy: Critical value (z*) for a given confidence level
- Khan Academy: Determining sample size based on confidence and margin of error
- Khan Academy: Conditions for valid t intervals
- Khan Academy: Interpreting confidence level example
- Khan Academy: Introduction to t statistics
- Khan Academy: Confidence interval simulation
- Khan Academy: Simulation showing value of t statistic
- Khan Academy: Confidence interval for a mean with paired data
- Khan Academy: Confidence intervals and margin of error
- Khan Academy: Example constructing and interpreting a confidence interval for p

- Tests of Significance
- Hypothesis Testing
- Khan Academy: P-values and significance tests
- Khan Academy: Introduction to power in significance tests
- Khan Academy: Hypothesis testing and p-values
- Khan Academy: When to use z or t statistics in significance tests
- Khan Academy: Examples thinking about power in significance tests
- Khan Academy: Conditions for a z test about a proportion
- Khan Academy: Writing hypotheses for a significance test about a mean
- Khan Academy: Constructing hypotheses for a significance test about a proportion
- Khan Academy: Free response example: Significance test for a mean
- Khan Academy: Example calculating t statistic for a test about a mean
- Khan Academy: Comparing P-values to different significance levels
- Khan Academy: Calculating a z statistic in a test about a proportion
- Khan Academy: Conditions for a t test about a mean
- Khan Academy: Introduction to Type I and Type II errors
- Khan Academy: Comparing P-value from t statistic to significance level
- Khan Academy: Examples identifying Type I and Type II errors
- Khan Academy: Calculating a P-value given a z statistic
- Khan Academy: Making conclusions in a test about a proportion
- Khan Academy: Examples of null and alternative hypotheses
- Khan Academy: Idea behind hypothesis testing | Probability and Statistics | Khan Academy
- Khan Academy: Estimating a P-value from a simulation
- Khan Academy: Using a table to estimate P-value from t statistic

- Inference for Proportions
- Inference for Two-Way Tables
- Inference for Regression
- Small Sample Inference for One Mean

- Investigating Population Survey Data
- Applying central limit theorem to population means. Part 3
- Confidence intervals for population means. Part 1
- Confidence intervals for population means. Part 2
- Estimating population means (small samples). Part 1
- Estimating population means (small samples). Part 2
- Estimating population means (small samples). Part 3
- Estimating population means (large samples). Part 1
- Estimating population means (large samples). Part 2
- Estimating population means (large samples). Part 3
- Population mean and sample mean :
- Calculating means
- Khan Academy: Inferring population mean from sample mean
- Khan Academy: Sample vs. Population Mean
- Khan Academy: Standard error of the mea

- Comparing Two Means
- Khan Academy: Two-sample t test for difference of means
- Khan academy: Hypothesis test for difference of means
- Khan academy: Confidence interval of difference of means
- Khan academy: Difference of sample means distribution
- Khan academy: Calculating confidence interval for difference of means
- Khan academy: Constructing t interval for difference of means
- Khan academy: Conditions for inference for difference of means

- Applying central limit theorem to population means. Part 1
- Applying central limit theorem to population means. Part 2
- Khan Academy:Comparing population proportions 1
- Khan Academy: Hypothesis test comparing population proportions
- Khan Academy: Hypothesis test for difference in proportions example
- Khan Academy: Conditions for a z test about a proportion

- Khan Academy: Confidence intervals for the difference between two proportions
- Khan Academy: Examples identifying conditions for inference on two proportions
- Khan Academy: Calculating a confidence interval for the difference of proportions
- Khan Academy: Hypothesis test for difference in proportions
- Khan Academy: Comparing population proportions 1
- Khan Academy: Comparing population proportions 2
- Khan Academy: Constructing hypotheses for two proportions
- Khan Academy: Confidence interval for hypothesis test for difference in proportions

- Khan Academy: Dataset individuals and categorical variables
- Khan Academy: Identifying individuals, variables and categorical variables in a data set

- Choosing & Usng SourcesTutorials on finding and using info.
- Article Express / Interlibrary LoanRequest articles, conference papers, and even books (check OhioLINK first) when unavailable at OSU. Request scans of print-only journal articles available at OSU.