Data handling in reality Statistics Data handling in reality

Origin of the word statistics The word stems from German origins : “statistik” meaning state affairs It is the science of the collection of data(information) and the analysis thereof to answer a question. The answering of a question which serves as the purpose for the statistics is done through interpretation of the information collected.

The statistical cycle 1. Pose/Ask research question 2.Collect data* 3. Organise data 4. Represent data 5. Summary and analysis of data

1. Pose/Ask research question This requires a problem of interest that requires collecting information to support an answer e.g. I am interested in knowing if I will pass this grade at the end of the year. Question will I pass at the end of the year. Question has to be focussed and mean something “So what?” meaning can anything be taken from the question

2.1 Collect data Types of data that will be require do answer the question: Numerical: Continuous numerical data is obtained from measurements. These include decimal values, e.g. how much water you drink per day 1,3l, how much do you weigh, marks for a test. Discrete numerical data items of data which can only be whole numbers, e.g. how many followers you have on Instagram, what age are you. Population: this is the entire group about which the data is being collected Sample: if the population is too large it is impossible to collect data, with time and resource constraints. A sample is thus a collection of subjects chosen to represent a population. Important a sample has to be diversely spread so that the data collected can be as true a reflection of the population as possible.

2.2 Data Collection Data collection tools: the type of data which is required will determine which tool will better suit the process Questionnaires: a list of questions given to a group of people to gather information Interviews: an interview is where a data collector asks questions to people rather than giving the sheet to the person as in the questionnaire, this takes more time. Observations: requires the data collector to record events and observations on a recording sheet. Other tools include: database tables, general survey, case study.

3. Organise data This requires the data to be sorted and organised Categorical data can be sorted into categories, numerical data can be arranged The organised data is sorted into a frequency table, or; Group data is tabled in class intervals Class interval refers to the possible values occurring within grouping parameters This is used when working with data values of a large group

4. Represent data Trends are easily displayed when graphed(drawn) There are different types of graphs namely: Bar graph Histograms Pie charts Line graphs The graph needs to be labelled and clearly indicate what is being displayed From a visual representation the question should be answerable

5. Summarising/Analyse data Summarising identifies occurrences in specific areas of the data Measures of central tendency is used to summarise data and indicates the: Middle or centre value (median),: after sorting the data (total number of values +1)/2 Most occurring(mode) and: the value that occurs most in the data set Average(mean) of the data set: (sum of all values in data set/ total number of values in set) Measures of spread indicates how closely the data is spread: Range: (maximum value – minimum value)

Class Discussion the national distribution of deaths

Class activity 1 : National population You are given the population figure for the country every 5 years for the past 20 years (see next slide) Questions: 1.1 Form a research question to suit the information given 1.2 Identify how the data was collected 1.3 Organize, summarise and represent the data 1.4 What is the mean and the range spread for the data? 1.5 What comments can be made about the data relating to the provinces? 1.6 What is the highest population per province for every year given?

Analyse the most active police stations in the Eastern cape

Analyse the attempted murder and the murder statistics

Activity 2 Residential burglary in EC 2.1 What is a possible research question that was asked to collect this data 2.2 Which kind of data is being displayed? 2.3 Re-organize the data in a table displaying the percentage per precinct 2.4 Represent the data using a Bar chart 2.5 What is the Mean, Median, Mode and Range? 2.6 What assumptions can be made from the data?

Comparing residential burglary to non-residential