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 feature of statistical power analysis?

  • Alpha value (the more you try to avoid TI the harder it is to avoid TII)
  • Strength of the pattern (signal)
  • Not the type of test you are doing
  • Variability in the data
  • Measurement error (noise-unwanted variable)
  • Sample size
  • Statistical power analysis: is a thought experiment about making a TII error, if there is a difference, how likely is it that the difference we arose occured by chance and how likely can we detect it?
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Other questions in this quiz

2. Which is not a primary observation of the Central Limit Theory?

  • The standard error of the sampling distribution of the mean is much bigger than the population
  • Shape of sampling distribution of mean is normal
  • The mean of the sample distribution of mean, the average sample mean goes towards the true population mean
  • The standard deviation of the sampling distribution of the mean is much smaller than the standard deviation of the population

3. Which is not a feature of the F statistic graph?

  • The right-skew in the F-distribution remains, even for very large samples. Both the t and normal distributions are symmetrical.
  • F-TEST compares two variances to see whether one is significantly bigger than the other
  • F distribution is bounded at 0, with all F-values having to be positive. Both Z and t can be either positive or negative, and the normal and t distributions go to infinity in both directions, this is only true
  • When both d.f. values are small it is very right-skewed. When both are large it looks a bit like the normal distribution. When one is small and the other large you get intermediate forms.
  • F Test compares two means to see whether one is significantly different that the other
  • The shape of the curve is defined by the degrees of freedom. The F distribution takes two d.f. values

4. What is the definition of a critical value?

  • A value that distinguishes significant from non significant differences at a specified level of confidence
  • A value that distinguishes from the two non significant values
  • A value that distinguishes from the two significant values

5. What is the dummy variable?

  • The value that is used to represent the sum of the equation
  • It is shown by the subscript of j next to the sigma sign but not in the rest of the equation.
  • It is shown in the equation, in front of each variable
  • The value that is shown before the equation


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