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. Which is not a characteristic of an ANOVA I between country extreme example?

  • Country 2 = 6mm
  • SSE= 0 as there is variance within the countries variance
  • SSE= 0 as there is no variance within country variance as all the same
  • So all the variance is between the countries and not within them
  • Country 1 = 8mm
  • The overall mean is 10
  • When we can account for all the variance by using country means instead of overall means, the country means are significantly different.
1 of 20

Other questions in this quiz

2. Which explanation about hypothesis' is incorrect?

  • Alpha value is the critical level of probability, eg: 1 in 20
  • TYPE II ERROR is accepting the null hypothesis when the the alternative explanation is true.
  • Alternative hypothesis- there is a pattern
  • Null hypothesis- there is no pattern
  • Hypothesis- there is not pattern
  • TYPE I ERROR is accepting an alternative (more complex) explanation when the null hypothesis is actually true.

3. Which statement is incorrect about the FITTED VALUE?

  • The best our model can do is predict that any given rice grain’s length will not be the mean grain length of rice from the same country – as judged by the grains in our sample.
  • Our model uses this information, as best it can, to produce a prediction (fitted value) for any rice grain
  • These fitted values can be compared with the actual (or OBSERVED) values.
  • These values come from the best fit procedure, the mean is the single value that best describes the data, it fits the data better than any other single value

4. What does the sigma, E and numbers mean in a summation equation?

  • Sigma= sum, E= quantity and the numbers represent the reference number
  • Sigma= sum, E= equation and the number are the values
  • Sigma= sum, E= equal and the number represents how many to multiple by
  • Sigma= sum, E= algebra and the number shows the ranking of data

5. Why is range a good statistic?

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

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