Essay

Mean, Median, and Mode - Just as we have summary statistics like the mean, median, and mode to give us a sense of the 'central tendency' of a data set, we need a summary statistic that captures the level of dispersion in a set of data.

Mean – Generally used unless the has outliers or skewed dirstribution

Median – used when there are outliers or skewed data

Mode – when there is more than one peak (Bimodal Distribution)

Skewed – where the tail leads

* The mean > the median

Standard Deviation

* Large means that data are widely dispersed

* Small means that data is clustered close together

* Variance

* Sum the Square of the differences from each data point minus the mean

* (Data Point – Mean)2

* Sum them all for each data point and than divide by (n-1)

* Take the square root of the variance to find Standard Deviation

* a smaller standard deviation indicates that more data points are near the mean, and that the mean is more representative of the data.

Coefficient of Variation

* compare the standard deviation of the data to the data’s mean

* Coefficient of Variance = standard deviation / mean

Causality – scatter plots never prove that one variable causes another

Correlation Coefficient (# of absences and temperature outside)

* Give more weight to outlier data

* -1 or 1 shows a strong negative or positive linear relationship

Generating Samples – Unbiased and Representative

* Random Sample

* Sample Size

* Depends on the level of accuracy

* Size does not really matter as long as sample is representative of the entire population

* Response Rate

* Low response rate susceptible to Bias

* Demonstrate that non respondents opinions do not differ from those who responded

* Raise response rate

* Classic Mistakes

* Unrepresentative Sample

* Low response rate

* Biased respondents

* Biased Questions

Confidence Interval...