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Descriptive Statistics II: By the end of this class you should be able to:

Descriptive Statistics II: By the end of this class you should be able to:. describe the meaning of and calculate the mean and standard deviation of a sample estimate normal proportions based on mean and standard deviation plot a histograms with alternative scaling. Palm: Section 7.1, 7.2.

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Descriptive Statistics II: By the end of this class you should be able to:

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  1. Descriptive Statistics II:By the end of this class you should be able to: • describe the meaning of and calculate the mean and standard deviation of a sample • estimate normal proportions based on mean and standard deviation • plot a histograms with alternative scaling Palm: Section 7.1, 7.2 please download cordbreak1.mat & FWtemperature.txt

  2. Exercise • Download FWTemperature.txt • Read into MATLAB • Prepare a single figure with two plots • a histogram of March highs (row 2) • a histogram of April highs (row 4) • Label these plots fully • Print out the your commands and the resulting figure

  3. Review: Quantifying Variation Mean Central Tendency >> mean(x) Standard Deviation Spread >> std(x) difference  deviation of each point about the mean squared  all values positive Summation  yields one number Divide by n-1 normalize the sum for based on degrees of freedom

  4. The Normal (Gaussian) Distribution Mode (Population) Standard Deviation Mean

  5. Note on Sample and Population Statistics

  6. meanm Percentage of observations in the given range 68 %  1s 95.5 % 99.7%  2s  3s Expected Proportions for known 

  7. Expected Proportions for known  68 % 16 %

  8. Proportions Problem Data analysis of the breaking strength of a certain fabric shows that it is normally distributed with a mean of 200 lb and a variance (2) of 9. • Estimate the percentage of fabric samples that will have a breaking strength between 197 lb and 203 lb. • Estimate the percentage of fabric samples that will have a breaking strength no less than 194 lb.

  9. Review: Types of Histograms

  10. Additional Example (not covered in class)Looking at two sets of data • Look at a histogram of the second set of data, ‘cord2’ • How would you compare it to cord the first set of data? • What problems do you run into?

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