Advanced Statistics

Overview

Framework:
Access to HE 2024
Level:
Level 3
Unit No:
Not available
Credits:
6
Guided learning hours:
Not available

Qualification Grading Type

Graded

For the full unit details, please download the latest version of the qualification specification. This is available for download on the relevant qualifications page.

Unit Learning Outcomes

To view the assessment criteria and any additional content, please expand the relevant learning outcome below.

1. — Know about normal distribution.

Assessment Criteria

  • 1.1.

    Obtain percentages of a normal distribution using standard deviations.

  • 1.2.

    Explain what is meant by a skewed distribution.

  • 1.3.

    Calculate the z score.

  • 1.4.

    Use published tables for the normal distribution to calculate probabilities.

  • 1.5.

    Solve problems involving the sampling distribution of a statistic.

2. — Know about confidence interval estimation.

Assessment Criteria

  • 2.1.

    Explain the concept of a confidence interval.

  • 2.2.

    Obtain confidence intervals for a Normal mean with variance known.

3. — Know about the nature of hypotheses.

Assessment Criteria

  • 3.1.

    Classify tests as one-tailed or two-tailed.

  • 3.2.

    Formulate the experimental/alternative hypothesis and the corresponding null hypothesis.

  • 3.3.

    Explain which hypothesis is being tested.

  • 3.4.

    Distinguish between type 1 and type 2 error.

4. — Be able to solve problems using linear and multiple regression.

Assessment Criteria

  • 4.1.

    Solve problems involving linear regression.

  • 4.2.

    Solve problems involving multiple regression.

5. — Be able to use non-parametric tests.

Assessment Criteria

  • 5.1.

    Use the Wilcoxon and Mann Whitney tests correctly by:

    • a) calculating the statistic
    • b) locating the statistic in the tables and
    • c) drawing the correct conclusion.