Using Numeracy and Data for Research

Overview

Framework:
Access to HE 2024
Level:
Level 3
Unit No:
Not available
Credits:
3
Guided learning hours:
Not available

Qualification Grading Type

Ungraded

Unit Learning Outcomes

1.

Understand how to classify and represent data.

Classify different types of data. e.g. discrete, continuous quantitative, qualitative.

Produce a frequency distribution for both discrete and continuous data. For example, for discrete data, students could produce a discrete probability distribution table (e.g. frequency distribution of a 6 sided die or spinner). For continuous data, a group frequency distribution table could be created (e.g. grouped frequency distribution of the height of children in a class).   

Assessment Criteria

  • 1.1

    Classify data into to following categories:

    • discrete
    • continuous
    • quantitative
    • qualitative.

  • 1.2

    Create a frequency distribution for continuous and discrete data.

2.

Be able to carry out basic calculations.

Perform basic calculations such as converting fractions into decimals and decimals into percentages.

Calculate percentages e.g.

  • Calculating percentage of an amount (e.g. 15% of £240)
  • Percentage increase and decrease
  • Calculate percentage change. This could include calculating more than one percentage change.

Calculate probabilities e.g.

  • basic probability (the number of ways an event can occur/the total number of possible outcomes).
  • using ‘and’ rule to calculate probabilities for independent events
  • using ‘or’ rule to calculate probabilities for mutually exclusive events.
  • conditional probability
  • using visual representations to help calculator probabilities e.g.

○Sample space

○Tree diagrams

○Venn diagrams.

Assessment Criteria

  • 2.1

    Convert fractions into decimals and decimals into percentages.

  • 2.2

    Calculate percentages.

  • 2.3

    Calculate probabilities.

3.

Be able to calculate and analyse descriptive statistics.

Analyse two data sets using descriptive statistics:

Measures of central tendency:

  • mean
  • median
  • mode

Measures of dispersion e.g.

  • range
  • interquartile range
  • standard deviation

Standard error. 

Assessment Criteria

  • 3.1

    Calculate measures of central tendency (mean, median and mode).

  • 3.2

    Calculate measures of dispersion (e.g. range, interquartile range and standard deviation).

  • 3.3

    Calculate standard error.

  • 3.4

    Analyse two data sets using the basic descriptive statistics above.