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Statistical Significance: Little Quick Fix

by John MacInnes SAGE Publications Ltd
Pub Date:
Pbk 124 pages
AU$19.99 NZ$19.99
Product Status: In Stock Now
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Statistical significance: In the ‘Stats Fix' section of the series, each title will tackle a skill or concept that students need extra, quick help getting their heads round. Statistical significance is a key challenge. This title can be seen as the next ‘big' concept to grasp after probability. You can't get anywhere in your statistics course without grasping statistical significance. Students think it's hard, and pretend to understand. It is actually a straightforward concept everyone can - and should - understand. Do your results mean something - or not? How can you measure it? Breaking it down into three building blocks, this LQF shows students how to master: - hypothesis testing - normal distribution - p values Students will learn how to understand the concept, and also how to explain it for maximum effect in their essays and lab reports. Good for results - this is also a secret weapon for critical thinking.

Section 1: What is statistical significance and inference?
Section 2: Why do I have to draw a random sample?
Section 3: What is a normal distribution?
Section 4: What is a standard error?
Section 5: How do I calculate confidence intervals with standard errors?
Section 6: What is a p-value?
Section 7: What does a significant p-value actually mean?

John MacInnes is Professor of Sociology at the University of Edinburgh. He has been teaching students quantitative methods and data analysis for thirty years. He has been Strategic Advisor to the UK Economic and Social Research Council on Quantitative Methods Training and currently advises the British Academy on quantitative skills, the UK Q-Step programme on statistics pedagogy and researches on statistics anxiety for the ESRC National Centre for Research Methods. He is a Fellow of the Academy of Social Sciences and the Royal Statistical Society, where he is a member of it Council.  His own research and publications range over population ageing and demographic change, gender identity, national identity and the sociology of industry.