10,95 €
10,95 €
inkl. MwSt.
Sofort per Download lieferbar
payback
5 °P sammeln
10,95 €
10,95 €
inkl. MwSt.
Sofort per Download lieferbar

Alle Infos zum eBook verschenken
payback
5 °P sammeln
Als Download kaufen
10,95 €
inkl. MwSt.
Sofort per Download lieferbar
payback
5 °P sammeln
Jetzt verschenken
10,95 €
inkl. MwSt.
Sofort per Download lieferbar

Alle Infos zum eBook verschenken
payback
5 °P sammeln
  • Format: PDF

Lecturers 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
…mehr

Produktbeschreibung
Lecturers 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.

  • 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.

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, D ausgeliefert werden.

Autorenporträt
Maureen is a lecturer in Early Childhood Studies and the course leader for the MA Childhood Studies at the University of Suffolk.

In 2010, Maureen graduated from Marian University in Indianapolis, Indiana with a BA in Sociology and Political Science. In 2012, she received her MA Sociology at University of Essex. Following the completion of her postgraduate degree, Maureen collaborated on an ESRC-funded project hosted by the UK Data Service called Digital Futures, which looked at methodological issues surrounding data management and re-use of qualitative datasets. Maureen is a member of the Social Research Association, British Sociological Association, and American Sociological Association.

Maureen's research interests focus generally on sociological perspectives of subjectivity, identity, constructions of the body, and reproductive politics. She is particularly interested in theorisations of pregnant bodies and bodies of unborn children, and how these understandings of bodies impact social policies. Maureen also has an interest in methodological and ethical issues of re-using data. She currently holds a research position at the UK Data Service which looks at the ethics of data sharing and using data for teaching.