Statistical Analysis Quantitative Data Research · Statistical, mathematical or computational investigation of observable phenomena · Uses numerical data to draw inferences/conclusions · Its process of collecting, analysing and interpreting numerical data · Used to find patterns, averages, predictions, causal relationships and generalise results to wider populations Philosophical Lense · Quantitative research belongs to positivism paradigm of research philosophy · Social reality based on understanding of human behaviour through observation and reasoning · True knowledge can be observed through observation and experiment including measurement and quantitative analysis · Research depends on quantifiable observations which leads to statistical analysis · Researcher is independent of research and there's no provisions of human interest in the study Quantitative Research Approach . Intro · Literature review o Theoretical review o Hypotheses o Conceptual model/framework · Data collection and analysis · Descriptive analysis · Inferential statistics · Discussion and conclusion General Terms · n= number of observations variables= data measures that can vary · dependent variable= the outcome which is affected by independent variable · independent variable= a variable that changes which affects dependent variable · hypothesis= a statement to be tested · significance= expresses our confidence in our results not happening by chance · primary data= surveys using questionnaires, interviews and experiment · secondary data= databases, reports, electoral statics, housing data Levels of Measurement Nominal-level data: observations can only be classified, no order relation available Ordinal-level data: observations can be classified and ordered Inter-level data: observations can be classified, ordered and gaps among the different categories are meaningful, however 0 has no meaning and is just a convenient starting point
Ratio-level data: observations can be classified, ordered and gaps among the different categories are meaningful and 0 has a proper meaning Types of Statistics 1. Descriptive statistics-> methods of organising, summarising and presenting data in an informative way 2. Inferential statistics-> the methods used to estimate a property of a population on the basis of a sample Descriptive Statistics · Describe or summarise data · Used to describe basic features of the data in a study, they provide simple summaries about sample and the measures · Together with simple graphical analysis they form basis of every quantitative analysis of data Ways of describing data · Bar chart: way of summarising categorical data, displays data using bars · Histogram: it's a graphical representation which organises a group of data points into specific ranges · Line graph: type of chart which shows info changing Measures of central tendency · Mean- add up values in set and divide by how many there are · Median- middle value in data set . Mode- value in data set which occurs the most Measures of dispersion · Range- the difference between the min and max values in a set, highest number minus lower number · Standard deviation- number that conveys how much the values in a set differ from its mean, this is the same units as the mean so is normally used to show dispersion · Variance- conveys spread of