Data presentation and interpretation - Topic 2 Flashcards
Interpret single-variable diagrams, scatter diagrams and regression lines, interpret measure of central tendency, and recognise outliers & clean data
Year 1 - Chapter 3.2
What makes a box plot useful in data representation?
A box plot can be drawn to represent important features of the data. It shows the quartiles, maximum and minimum values and any outliers.
Year 1 - Chapter 3.3
When are cumulative frequency graphs useful?
If you are given data in a grouped frequency table and you aren’t able to find the exact values of the median and quartiles.
Year 1 - Chapter 3.4
How else can grouped frequency tables be presented?
A histogram. It gives a good picture of how the data is distributed and enables you to see a rough location, the general shape and how spread out the data is.
Year 1 - Chapter 3.4
How do you calculate frequency density?
The vertical scale on a histogram shows the frequency density:
Frequency Density = Frequency/Class Width
Joining the middle of the top of each bar in a histogram with equal class widths forms a frequency polygon.
Year 1 - Chapter 3.5, 2.1 & 2.4
Where should you comment on when comparing data?
- A measure of location - A single value which describes a position in a data set
- A measure of spread - A measure of how spread out the data is
Year 1 - Chapter 2.1
What is a measure of central tendency?
If the single value in measure of location describes the centre of data.
Year 1 - Chapter 2.5
How is variance calculated?
Variance = (Σ(x-x̄)²)/n = (Σx²)/n - (Σx/n)² = Sₓₓ/n,
where Sₓₓ = (Σ(x-x̄)²) = Σx² - (Σx)²/n
Year 1 - Chapter 2.5
How is standard deviation calculated?
Standard deviation is the square root of variance
σ = √((Σx²)/n - (Σx/n)²)
Year 1 - Chapter 3.1
What is the common definition of an outlier?
value > Q₃ + k(Q₃-Q₁)
value < Q₁ - k(Q₃-Q₁)
Year 1 - Chapter 4.1
When is it appropriate to represent bivariate data?
In a scatter diagram, with the independent variable on the x-axis and the dependent variable on the y-axis.
Year 1 - Chapter 4.1
What does correlation describe?
The nature of the linear relationship between two variables. When one variable causes a change in the other, the relationship is called causal. When two variables are correlated, you must consider the context of the question and use common sense to determine the causality of the relationship.
