Year 12 Unit 3 General Maths Recap

During a hybridisation experiment a scientist counted the tall and dwarf marigold plants. This is an example of:

• categorical data

• nominal data

• discrete data

• continuous data

A researcher took 100 blood samples from a group of volunteers. He wanted to determine if there is a relationship between the amount of iron present in the blood and the amount of vitamin C present in the blood. Choose the option below that describes the best method of displaying his results.

• Stem and leaf plot

• Line graph

• Two-way frequency table

• Scatterplot

The following two-way frequency table shows the composition of left- and right-handed students in Years 11 and 12 at a school. The percentage of all left-handers who are in Year 11 is closest to:

• 6.8%

• 12.5%

• 14.3%

• 40%

What type of correlation does an r-value of 0.64 indicate?

• Strong, positive correlation

• Strong, negative correlation

• Moderate, positive correlation

• Moderate, negative correlation

A gardener tracks a correlation coefficient of 0.79 between the growth rate of his trees and the amount of fertiliser used. What can the gardener conclude from this result?

• The growth rate of the trees is influenced by the amount of fertiliser used

• An increase in tree growth increases the use of fertiliser

• There is no correlation between the growth rate of the trees and the amount of fertiliser used

• The growth rate of the trees influences the quality of the fertiliser used

When y=0.54+15.87x, the value of y when x=2.5 is:

• 18.91

• 40.215

• 39.135

• 6.888

A series of data points recorded a coefficient of determination value of 0.82. Calculate Pearson’s correlation coefficient.

• 82%

• 0.18

• 0.67

• 0.91

The deseasonalising process on time series data is used to:

• smooth out irregular fluctuation

• determine if there is an upward trend

• determine if there are any patterns in the data

• remove any seasonal trends

The above table shows the seasonal indices from a time series. The value of the seasonal index for quarter 3 is:

• 102

• 0.98

• 1.19

• 1.00

Using the seasonal indices above, a seasonally adjusted value for quarter 1, when the original value was 445, is closest to:

• 436

• 454

• 484

• 650