For unlimited access to Textbook Notes, a Class+ subscription is required.
- 2 reasons for using statistics
o Statistics are used to describe date
o Used to make inferences on the basis of the sample data about a population
- 4 scales of measurement
o Nominal – have no numerical, quantitative properties. It is simply different categories or
groups. Most independent variables in experiments are nominals. Ex: eye colour, birth
o Ordinal - involve minimal quantitative distinction. We can rank order the levels of the
varable being studied from lowest to highest. Ex: most important problem to least
importance such as gang violence could be the first one.
o Interval & Ratio - have much more detailed quantitive properties. With an interval
scale, the intervals between the levels are equal in scale. In ratio scale variables, they
have both equal intervals an an absolute zerio point that indicates the absence of the
variable being measured. Ex: time, weight , length.
- Depending on th way that the variables are studied, there are 3 basic ways of describing the
o Comparative group percentages - for example you want to find out whehter males r
females differ in the interest in travelling. So after getting the reults, you calculate it inro
percentage. NOTE: we are focusing on percentage because the travel variable is
o Correlating scores of inviduals on two variables - this is when you do not have distinct
groups od subjects. Due to this, individuals are measured on two variables and each
variable has a range of numerical values.
o Comparing group means – to compare the mean responses of pariticipants in two or
- Frequency distribution indicates the number of individuals that receive each possible score on a
Graphing Frequency distributions
- Pie Charts – are particularly useful representing nominal scale information. Overall, pie charts is
when you divide a whole circle or pie into slices that represent relative percentages.
- Bar Graphs
- Frequency Polygons – this is most useful when the data represent interval or ratio scales.
- Histograms – uses bars to display a frequency distribution for a quantitative variable.
- Descriptive statistics allow researchers to make precise statements about the data.