Interpreting Geographical Data

Year one statistics exam

  • Summation sign
  • Rounding
  • Central tendency
  • Variability
  • Boxplots
  • Standard deviations
  • Normal distribution
  • Sampling
  • Reliability and standard errors
  • Confidence intervals and t-distribution
  • Colomn, charts and tables
  • Hypothesis testing and one sample t-test
  • Two sample t-test
  • F-test
  • Anova I
  • Anova II
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  • Created by: Sophie
  • Created on: 04-01-15 13:38

1. Define inference

  • The application of probability levels to statements made about the sample and whether they fit with the true population parameters
  • The process of moving from info about samples to statement about population
  • Statistical methods used to make statements about the poplation
  • Statistics from samples for population
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Other questions in this quiz

2. What does a Poisson frequency distribution graph show?

  • Unusual things
  • Usual things
  • Non existent events
  • Constant things

3. Which statement is incorrect about how we measure reliability?

  • One of the characteristics affecting this measure is sample size, the bigger the sample size the more confident we are so there is less unreliability
  • Unreliability= sqrt(variance/N) which is known as the Standard Error of the mean
  • We actual measure it through unreliability
  • The variability of the data, because the more variable the data is the less confident we are so there is more unreliability
  • Unreliability is not proportional to the sample standard deviation divided by the sample size
  • The sample size is square rooted, and because standard deviation is the square root of variance so they are both square rooted.

4. What do you do when asked to round off?

  • Leave it as it is
  • Round up
  • Your round up or down depending on what distorts the data the most
  • Round down

5. Why is range a good statistic?

  • Focus' on 50% of the data around the mean
  • Extreme values are not ignored
  • Extreme values are ignored
  • Focus' on 50% of the data around the extreme values

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