presenting data

forms of data

• quantitative (numbers) vs qualitative (opinions)

• structured (tables) vs unstructured (images)

why does presenting data matter

• see the bigger picture- numbers become meaningful

• spot patterns and trends- helps identify growth, decline

• support better decisions- managers act with confidence

data in business

• Accounting - statistical sampling for auditing client companies

• Finance- analyse financial data of companies such as profit- investment decisions

• Marketing- forecast customer behaviour and product strategies

• Retail- anticipate customer demands and ensure merchandise is available when required

• Production - statistical process control to ensure production quality

data measurement

• Nominal- categories- (Green, Blue, Red)

• Ordinal- values ordered based on predefined criteria

• Interval- intervals between values mean something- (temperature)

• Ratio- intervals means something but 0 value isnt arbitrary- (profit)

presentation techniques

• Tally chart/ Frequency distribution - Count number of occurrences

• Bar charts- show frequency distribution, height=frequency, no touch/ Histogram- distribution of continuous data, touch

• Pie chart- how a total is divided into parts, not suitable for too many variables

• Line charts- show how a variable changes over time, independent= x, dependent= y

• Scatter graphs- points are plotted not joined, rls between 2 variables

stem and leaf diagram

• retains ordinal data values

• makes it easy to calculate measures and assess the shape of the distribution

• “0” to denote leaves between 0 and 4

• “*” to denote leaves between 5 and 9