**Descriptive Statistics**

*Standard Deviation (S.D. or o)*- Average deviation of each observation from precise centre of all weighted observations, but sensitive to relative weights of observations.
- Indicates how dispersed points are from the mean
- More precise than mean deviation; preferred.

- Average deviation of each observation from precise centre of all weighted observations, but sensitive to relative weights of observations.
- Example:
- David Demers….
- N = 198 newspapers
- M = 2.64 editorials
- o = +/- 1.84
- Range = 0 – 8
- Standard deviation tells us that the amount of editorials/paper is not around 2.64, but between the dispersion of 0.8 and 4.48 (2.64 +/- 1.84)

- David Demers….

Bivariate Statistics

- Analysis of two sets of data
- Coefficient of Correlation
- Indicates extent to which ordered pairs of observations share variance
- It gauges if the behaviours of two phenomena are related.
- Example
- If x happens, does y happen?
- If x happens, how much does y happen?

- For correlation and scatter points:
- Ordered pair = two related numbers (x, y)
- Examples:
- (x,y) [scatter plot of x and y analysis, use excel]
- Hours of television, hours of radio
- Age, hours of television
- Education (coded?), hours of radio
- Age, education.

- (x,y) [scatter plot of x and y analysis, use excel]

- Coefficient of correlation or Pearsons r
- “Coefficient” = measure of strength of correlation expressed as r = + z or – z
- 0-10 (no correlation)
- 10-30 (slight degree of relationship)
- 30-50 (fair degree of relationship)
- Common knowledge…

- “Coefficient” = measure of strength of correlation expressed as r = + z or – z
- Descriptive Statistics àCorrelation of Coefficient
- Can do
- Flag significant data (e.g. highs, lows, averages)
- Reveals patterns
- Suggests relationships between values
- Indicate strength relationship between two values

- Can’t do
- Provide explanations
**You must provide the explanation**

- Can do

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