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How to think about statistics

저자: John L Phillips
출판사: New York : W.H. Freeman, ©1988.
시리즈: Series of books in psychology.
판/형식:   Print book : 영어 : [3rd ed.]모든 판과 형식 보기
데이터베이스:WorldCat
요약:
You can be informed by statistics or fooled by them, but you can't escape them - not in today's society. Here's your chance to learn what they mean. How to Think about Statistics is a common-sense introduction to the logic behind statistical analysis and problem solving. Instead of focusing on numerical computations, it emphasizes the thinking behind the numbers and shows you how statistics are applied in such  더 읽기…
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자료 유형: 인터넷 자료
문서 형식: 책, 인터넷 자원
모든 저자 / 참여자: John L Phillips
ISBN: 0716719231 9780716719236 0716719223 9780716719229
OCLC 번호: 16089215
메모: Revised edition of: Statistical thinking. 2nd ed. c1982.
설명: xiv, 198 pages : illustrations ; 24 cm.
내용: 1. Introduction --
The task --
The basic ideas --
Facing mathphobia --
2. Frequency distributions --
Normal distributions --
Skewed distributions --
Other configurations --
Summary --
3. Measures of central tendency --
The mean (x̄) --
The median (Mdn) --
The mode --
Summary --
Sample applications --
4. Measures of variability --
The standard deviations (S) --
The semi-interquartile range --
The range --
Degrees of freedom --
Summary --
Sample applications --
5. Measures of relationship --
The rank-difference coefficient (p) --
The product-moment coefficient (r) --
Effect of restricted variability --
Correlation and causation --
Reliability and validity --
Summary --
Sample applications --
6. Interpreting individual measures --
Standard scores: The z scale --
Other standard scores --
Standard scores in correlation --
Centile (or "percentile") scores --
Age and grade norms --
Summary --
Sample applications --
7. Precision of measurement --
Standard errors --
Confidence intervals and levels of confidence --
Effect of N on standard error --
Two ways of quantifying reliability --
Expectancy tables --
Summary --
Sample applications --
8. Significance of a difference between two means --
An example --
Test of significance: The z ratio --
Test of significance: The t ratio --
Significance levels --
A common misinterpretation --
One- versus two-tail tests --
Statistical versus practical significance --
Summary --
Sample applications --
9. More on the testing hypotheses --
Comparison of frequencies: Chi-square --
Multimean comparisons: Analysis of variance --
Summary --
Sample applications --
10. Another look at correlation and causation --
Correlational versus experimental studies --
Continuous versus discontinuous variables and measurements --
Correlation as an index of causation --
Summary --
11. Summary.
일련 제목: Series of books in psychology.
책임: John L. Phillips, Jr.

초록:

You can be informed by statistics or fooled by them, but you can't escape them - not in today's society. Here's your chance to learn what they mean. How to Think about Statistics is a common-sense introduction to the logic behind statistical analysis and problem solving. Instead of focusing on numerical computations, it emphasizes the thinking behind the numbers and shows you how statistics are applied in such fields as psychology, education, politics, sociology, and social work. -- from back cover.

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