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In these uncertain times, how much can you trust health news? Is the research behind breaking headlines reliable? This book is an indispensable resource for students and general readers, helping them evaluate and think critically about health information. "People Who Drink Coffee Live Longer." "Students Learn Better When Listening to Classical Music." "Scientists Discover the Gene That Causes Obesity." We are constantly bombarded with reports of "groundbreaking" health findings that use attention-grabbing headlines and seem to be backed by credible science. Yet many of these studies and the news articles that discuss them fall prey to a variety of problems that can produce misleading and inaccurate results. Some of these may be easy to notice—like a research study on the benefits of red meat funded by the beef industry, or a study with a sample size of only 10 people—but others are much harder to spot. Skewed Studies: Exploring the Limits and Flaws of Health and Psychology Research examines the most pervasive problems plaguing health research and reporting today, using clear, accessible language and employing real-world examples to illustrate key concepts. Beyond simply outlining issues, it provides readers with the knowledge and skills to evaluate research studies and news reports for themselves, improving their health literacy and critical thinking skills.
This book reviews the state-of-the-art advances in skew-elliptical distributions and provides many new developments in a single volume, collecting theoretical results and applications previously scattered throughout the literature. The main goal of this research area is to develop flexible parametric classes of distributions beyond the classical no
If you listen to any political argument, you're eventually bound to hear something like: "The science is settled on this." Or: "Just look at the statistics!" Or: "There have been studies that say..." You'd think we were living in the golden age of science and reason. But the truth is far more sinister, says Austin Ruse. We're actually living in the age of the low information voter, easily mislead by all-too-convincing false statistics and studies. In Fake Science, Ruse debunks so-called "facts" used to advance political causes one after the other, revealing how poorly they stand up to actual science.
1.Statistics : Meaning, Nature and Limitations, 2 .Statistics : Scope and Importance, 3. Statistical Investigation, 4. Types and Collection of Data, 5 .Questionnaire and Schedule, 6 .Sample Survey, 7 .Editing of Collected Data , 8. Classification and Tabulation of Data, 9. Diagrammatic Presentation of Data, 10. Graphic Presentation of Data, 11. Construction of Frequency Distribution, 12. Measures of Central Tendency , 13. Geometric Mean and Harmonic Mean, 14. Partition Values, 15. Measures of Dispersion, 16. Measures of Skewness, 17. Moments, 18. Measures of Kurtosis, 19. Correlation, 20. Index Numbers , 21. Analysis of Time Series , 22. Interpolation and Extrapolation, 23. Regression Analysis , 24. Probability Theory, 25. Probability Distributions or Theoretical Frequency Distributions, 26. Association of Attributes , 27. Sampling Theory and Tests of Significance , 28. Chi-Square Test and Goodness of Fit, 29. Analysis of Variance , 30. Statistical Quality Control, Appendix.
BUSINESS MATHEMATICS 1. Arithmetic Progression, 2. Geometric Progression, 3. Harmonic Progression, 4. Simple Interest, 5. Compound Interest, 6. Profit and Loss, 7. Percentage, 8. Stock and Shares, 9. Discount, 10. Present Value, 11. Ratio and Proportion, STATISTICS 1. Statistics : Meaning, Nature and Limitations, 2. Statistics : Scope and Importance, 3. Statistical Investigation, 4. Types and Collection of Data, 5. Questionnaire and Schedule, 6. Sample Survey, 7. Editing of Collected Data, 8. Classification and Tabulation of Data, 9. Diagrammatic Presentation of Data, 10. Graphic Presentation of Data, 11. Construction of Frequency Distribution, 12. Measures of Central Tendency, 13. Geometric Mean and Harmonic Mean, 14. Partition Values, 15. Measures of Dispersion, 16. Measures of Skewness, 17. Moments, 18. Measures of Kurtosis, 19. Correlation, 20.Index Number. Appendix (Log-Antilog Table).
1. Statistics : Meaning, Nature and Limitations, 2. Statistics : Scope and Importance, 3. Concept of Population and Sample, 4. Types and Collection of Data, 5. Construction of Frequency Distribution, 6. Measures of Central Tendency, 7. Geometric Mean, 8. Measures of Dispersion, 9. Measures of Skewness, 10. Measures of Kurtosis, 11. Probability Theory, 12. Probability Distribution or Theoretical Frequency Distribution, 13. Sampling Theory and Tests of Significance, 14. Correlation, 15. Regression Analysis
1.Statistics : Meaning, Nature and Limitations , 2 .Statistics : Scope and Importance, 3 .Types and Collection of Data (Univariate, Bivariate, Multivariate,Time Series and Cross Section Data), 4. Classification and Tabulation of Data , 5. Graphic Presentation of Data , 6 .Measures of Central Tendency , 7. Measures of Dispersion, 8. Measures of Skewness, 9. Measures of Kurtosis, 10. Correlation, 11. Index Number.
An excellent book for commerce students appearing in competitive, professional and other examinations. 1. Statistics : Meaning, Nature and Limitations, 2. Statistics : Scope and Importance, 3. Statistical Investigation, 4. Types and Collection of Data, 5. Questionnaire and Schedule, 6. Sample Survey, 7. Editing of Collected Data, 8. Classification and Tabulation of Data, 9. Diagrammatic Presentation of Data, 10. Graphic Presentation of Data, 11. Construction of Frequency Distribution, 12. Measures of Central Tendency, 13. Geometric Mean and Harmonic Mean, 14. Partition Values, 15. Measures of Dispersion, 16. Measures of Skewness, 17. Moments, 18. Measures of Kurtosis, 19. Correlation, 20. Index Number, 21. Analysis of Time Series, 22. Interpolations and Extrapolation, 23 . Regression Analysis, 24. Probability Theory, 25. Probability Distributions or Theoretical Frequency Distributions, 26. Association of Attributes, 27 . Sampling Theory and Tests of Significance, 28. Chi-Square Test and Goodness of Fit, 29. Analysis of Variance, 30 . Statistical Quality-Control (SQC).
1. Measures of Central Tendency 2. Geometric Mean and Harmonic Mean 3. Partition Values 4. Measures of Dispersion 5. Measures of Skewness 6. Measures of Kurtosis 7. Correlation 8. Index Number 9. Analysis of Time Series 10. Regression Analysis 11. Probability Theory 12. Probability Distributions or Theoretical Frequency Distribution Appendix (Log-Antilog Table)
An excellent book for commerce students appearing in competitive, professional and other examinations. Business Statistics 1.Statistics : Concept, Nature and Limitations, 2.Statistics : Scope and Significance, 3.Types and Collection of Data, 4. Classification and Tabulation of Data, 5. Frequency Distribution, 6. Graphic Presentation of Data, 7. Measures of Central Tendency (Mean, Median, Mode), 8. Measures of Variation or Dispersion (Rang, Q. D., M. D. & S. D.), 9. Measures of Skewness, 10. Measures of Kurtosis, 11. Correlation, 12. Regression Analysis, 13. Probability Theory, 14. Probability Distributions (Binomial, Poisson and Normal), 15. Sampling Theory and Tests of Significance. 16. Appendix. SYLLABUS Unit I : Statistics : Concept, Significance & Limitation, Type of Data, Classification & Tabulation, Frequency Distribution & Graphical Representation. Unit II : Measures of Central Tendency (Mean, Median, Mode), Measures of Variation : Significance & Properties of a Good Measure of Variation : Range, Quartile Deviation, Mean Deviation and Standard Deviation, Measures of Skewness & Kurtosis. Unit III :Correlation : Significance of Correlation, Types of correlation, Simple Correlation, Scatter Diagram Method, Karl Pearson Coefficient of Correlation. Regression : Introduction, Regression Lines, Regression Equation & Regression Coefficient. Unit IV :Probability : Concept, Events, Addition Law, Conditional Probability, Multiplication Law & Baye’s Theorem [Simple Numerical], Probability Distribution : Binomial, Poisson and Normal. Unit V : Sampling Method of Sampling, Sampling and Non-Sampling Errors. Test of Hypothesis, Type-I and Type-II Errors, Large Sample Tests.