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
- Created by: Sophie
- Created on: 04-01-15 13:38
Other questions in this quiz
2. How do we calculate a confidence interval?
- By calculating a range within which we are confident that the true mean lies
- By calculating the mean which we know the true population mean will show too
- By calculating the IQR which we are confident that the true median will be found
3. How do you calculate the error of variance?
- Error df= N-K to calculate the error variance of SSE/(N-K)
- The error is what is left unexplained after fitting the model. In the model, we have estimated one mean for each category, so:Number of parameters estimated = Kwhere K is the number of categories.
- SSEx(N-K)
4. Which statistic is more sensitive to extreme values?
- The mean and not the median or mode
- The median and not the range or mode
- The mode and not the mean or median
- The range and not the median or mode
5. Which is not a feature of how do you calculate the model variance?
- In the model, each category has a mean. So we move from the null model, which is just the overall mean (i.e. one parameter estimated from the data) to a mean for each category (i.e. K parameters estimated from the data). K-1
- Model variance = SSM x (K-1)
- Model df = (N – 1) – (N – K).That is N – 1 – N + K, so it simplifies to:Model df = K – 1.
- Model df is the number of categories minus one.
- Model variance = SSM ÷ (K – 1)
- The model df are the difference between the total df and the error df
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