STA10003 WEEK 1 TERMINOLOGY USED IN STATISTICS Statistics - Used as an overarching term to include the procedures and techniques that are used to organise, summarise and interpret information collected - Within states, further terminology is used such as populations, samples, variables Population - All things we are interested in Population parameter (describes entire population) - - measurement value (size) of population Sample - Subset of population - Sample statistic (describes sample) Variable - Piece of information we are wanting to measure (gender, age, ethnicity) Descriptive vs inferential statistics Descriptive - Organise raw info into manageable information - Numerical or graphical form (household size, most population type) Inferential - Techniques to allow us to use a sample statistics to generalise to make conclusions about the population (hypothesis testes, confidence intervals) Sampling error - natural discrepancy existing between the sample statistics and the population parameter Sample statistic can provide us with an estimate of the population parameter
TYPES OF RESEARCH METHODS Descriptive - When we just want to find something 'out' - (age of student) Correlational research - Want to explore a relationship between two or more variables - Is there a relation between height and weight, what can we infer from this? Comparative research - When we want to compare two or more groups on the same measure - Do part time students spend more hours working than full time Experimental method - Allows cause and effect explanation - One variable IV is causing a change in the other DV - IV - predictor fi explanatory - DV - outcome fi response - 'the IV is manipulated and the DV is observed fi measured' Non-experimental method - Does not allows cause - effect explanation - Both variables are observed fi measured - Correlational research - no manipulation - Non-equivalent groups (IV not manipulated) - Pre - post students - DV is measured twice at different times - IV - gender fi 'quasi independent variable' - DV - income
VARIABLES AND MEASUREMENT Overarching label of the element fi feature we want to measure Discrete - Separate categories (no intermediate values between) - 'countable' number of values - Examples - Number of children - Number of test questions Continuous - Infinite number of values that fall between two observedfi measureable values - Divisible into an infinite number of fractional parts - Example - Age 25, 19 - Distance travelled Measurement Categorical Nominal - used to label (name the group) 1= male, 2 = female Ordinal - used to label AND order 1,2,3,4 in a race. Chapter 1, chapter 2, chapter 3, in a text Metric Interval - numbers are used to label and order AND the intervals between the numbers are equal e.g. temperature in degrees of Fahrenheit Ratio - numbers are used to label and order and the intervals between the numbers are equal AND ERO means a complete absence of something eg. Number of correct answers in a test