Statistics: The Conceptual Approach - Softcover

Iversen, Gudmund R.; Gergen, Mary

Softcover

ISBN 10: 1461222451 ISBN 13: 9781461222453

Verlag: Springer, 2014

Inhaltsangabe

1 Statistics: Randomness and Regularity.- 1.1 Statistics: What's in a word?.- 1.2 Knowing how statistics is used: Goals for the reader.- Understanding what can go wrong.- Understanding statistical terms.- 1.3 Central ideas in statistics.- Randomness and regularity: Twins in tension.- Randomness in regularity.- Two examples in the study of randomness and regularity.- Probability: What are the chances?.- Variables: The names we give things.- Variables, values, and elements.- Theoretical variables and empirical variables.- Constants.- 1.4 Users of statistics.- 1.5 Relationship of statistics to mathematics, pencils, and computers.- 1.6 Summary.- Additional Readings.- Exercises.- 2 Collection of Data.- 2.1 Defining the variables.- 2.2 Observational data: Problems and possibilities.- Population versus sample.- Selection of the sample: Making sure the pot is stirred.- Random sample: What is it?.- Convenience sample: How to produce a "poor" sample.- Selecting proper samples.- Selection of variables on which to collect observational data.- 2.3 Errors and "errors" in collecting observational data.- Sampling error: The "error" that is not a mistake.- Nonresponse error: Result of rude, rushed, and reticent respondents.- Response errors.- 2.4 Experimental data: Looking for the causes of outcomes.- Experimental group and control group.- Selecting the experimental and control groups.- Problems with experimenting on people.- Role of statistics in experimentation.- Putting it all together: Does class size affect school performance?.- 2.5 Data matrix/Data file.- 2.6 Summary.- Additional Readings.- Exercises.- 3 Description of Data: Graphs and Tables.- 3.1 Graphs: Picturing data.- Creating statistical graphs.- Types of graphs.- 3.2 Categorical variables: Pie charts and bar graphs.- Graphing one categorical variable.- Graphing two categorical variables.- 3.3 Metric variables: Plots and histograms.- Graphing one metric variable.- Graphing two metric variables.- Time series plot.- 3.4 Creating maps from data.- 3.5 Graphing: Standards for excellence.- "The least ink": Is the simplest graph best?.- "Chartjunk": A new name for garbage.- Data density.- "Revelation of the complex".- 3.6 Tables: Turning can be timely.- 3.7 Summary.- Additional Readings.- Exercises.- 4 Description of Data: Computing Summary Statistics.- 4.1 Averages: Let us count the ways.- Mode: The hostess with the mostes'.- Median: Counting to the middle.- Mean: Balancing the seesaw.- Mode, median, or mean?.- 4.2 Variety: Measuring the spice of life.- Range: Lassoing the two extreme values.- Standard deviation: The crucial deviant.- 4.3 Standard error of the means.- 4.4 Standard scores: Comparing apples and oranges.- 4.5 Gain in simplicity, loss of information.- Replacing the data with a graph.- Replacing the data with a summary value.- 4.6 Real estate data: Out-of-sight prices.- 4.7 Summary.- Additional Readings.- Formulas.- Exercises.- 5 Probability.- 5.1 How to find probabilities.- Equally likely events.- Relative frequency.- Using subjective probabilities.- 5.2 Computations with probabilities.- Adding probabilities.- Multiplying probabilities.- 5.3 Odds: The opposite of probabilities.- 5.4 Probability distributions for discrete variables.- Binomial distribution.- Poisson distribution.- Hypergeometric distribution.- Displaying probabilities in graphs and tables.- Computations with probabilities.- 5.5 Probability distributions for continuous variables.- Standard normal distribution: The bell curve.- The t-distribution.- Chi-square distribution.- F-distribution.- Need for normally distributed data.- 5.6 Using probabilities to check on assumptions.- Is it a fair coin?.- Is it a fair workplace?.- Is it an evenly split electorate?.- 5.7 Decision analyis: Using probabilities to make decisions.- 5.8 Summary.- Additional Readings.- Formulas.- Exercises.- 6 Drawing Conclusions: Estimation.- 6.1 Sample statistic and population parameter.- 6.2 Point estimation.- What is a "good" point estima

Details zur Ausgabe

• Verlag: Springer
• Erscheinungsdatum: 2014
• ISBN 10: 1461222451
• ISBN 13: 9781461222453
• Einband: Paperback
• Sprache: Englisch
• Kontakt zum Hersteller: Nicht verfügbar