week 1 Flashcards
Population
the entire collection of interest, ie includes every single individual under banner
sample
random sample from population. hope is representative of population.
discrete variable
only a limited number of values possible eg. gender
continuous variable
many different values possible. eg age, anxiety score etc
categorical data
where subjects seperated into categories eg high/low anxiety. Number of subjects in category= frequency.
independent variable
is manipulated by the researcher so that measures pertaining to the DEPENDENT variable are derived
descriptive statistics
used to describe data. eg average, extreme scores etc
inferential statistics
used to infer something. If successful, research is used to infer something about a population.
nominal scales
labels. No meaningful way to describe difference or degrees between, just have distinct labels. eg religion type.
ordinal scales
Whilst responses are along a dimension, distances between scale values are unknown. eg life change stressors ocurring between 10 and 15 years are not necessarily of equal value as those occurring between 20 and 25 years.
interval scales
there are meaningful differences between points on the scale BUT CANNOT talk in terms of ratios. eg. temperature scale-where zero cannot be said to be an absence of temperature, nor can one say that 40 degreees is half as hot as 80 degrees.
ratio scales
the most informative scale of measurement. Can be used for ratios. has a true zero point
frequency distribution
records the frequency of each score
histogram
bar chart-graphical illustration of a frequency distribution
stem and leaf display.
table used to display data. eg Stem column may be 10’s and Leaf column units. Therefore if stem column reads 1 2 2 9, adjacent to Leaf column 7, this means 1 person scored 71, two people scored 72, and one scored 79.
