Description
Book SynopsisLecturers teaching big mixed cohort intro statistics courses cite one of the more frequent challenges their students encounter involves choices over which statistical test to use. Students, even if they have a basic grasp of statistics and which types of tests are out there, often make the wrong choice, or have difficulty in distinguishing between the types of tests for different types of data.
This Little Quick Fix provides step-by-step support in narrowing down possible tests they could use so they know which test fits their data and variables, and which test will actually help them answer the questions they want to answer and create maximum impact from their data.
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.
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Lively, ultra-modern design; full-colour, each page a tailored design.
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An hour′s read. Easy to dip in and out of with clear navigation enables the reader to find what she needs—quick.
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Direct written style gets to the point with clear language. Nothing needs to be read twice. No fluff.
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Learning is reinforced through a 2-minute overview summary; 3-second summaries with super-quick Q&A
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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.
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Checkpoints in each section make sure students are nailing it as they go and support self-directed learning.
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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 ContentsWhat kind of analysis can I run with descriptive statistics? How do I identify the level of measurement? What kind of analysis can I run with inferential statistics? What is the difference between paired and independent groups? How can I tell if my data is normally distributed? DIY section: How to assess your variables and data.
