You can′t get anywhere in your statistics course without grasping statistical significance. it′s often seen as difficult but 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 Little Quick Fix 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.
Little Quick Fix titles provide quick but authoritative answers to the problems, hurdles, and assessment points students face in the research course, project proposal, or design—whatever their methods learning is.
- Lively, ultra-modern design; full-colour, each page a tailored design.
- An hour′s read. Easy to dip in and out of with clear navigation enables the reader to find what she needs—quick.
- Direct written style gets to the point with clear language. Nothing needs to be read twice. No fluff.
- Learning is reinforced through a 2-minute overview summary; 3-second summaries with super-quick Q&A
- DIY tasks create a work plan to accomplish a task, do a self-check quiz, solve a problem, get students to what they need to show their supervisor.
- Checkpoints in each section make sure students are nailing it as they go and support self-directed learning.
- How do I know I’m done? Each Little Quick Fix wraps up with a final checklist that allows the reader to self-assess they’ve got what they need to progress, submit, or ace the test or task.
Table of Content
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?
About the author
From 2009 to 2014 John was the Strategic Advisor to the Economic and Social Research Council (ESRC) on quantitative methods training overseeing the genesis and launch of the Q-Step programme. From 2015 to 2020 he was Strategic Advisor to the British Academy on Quantitative skills and a member of the British Academy’s High Level Strategy group on Quantitative Skills. John is a Chartered Statistician and was Vice President (Professional Affairs) of the Royal Statistical Society 2019-20. He has held research grants from the European Commission, UK ESRC, British Academy, Leverhulme trust and British, Spanish and Catalan government departments.
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