Mario Orsi

Convert numbers greater than 1 into standard form/scientific notation.

This question assesses learners' basic knowledge of a one-way ANOVA and ability to interpret typical software output.

True/false question type to assess basic knowledge of multiple regression.

Interpreting the minitab output from a logistic regression model of salary against obesity as measured by BMI.

Adaptive marking is in place for Part b).

This question assesses the learner's ability to compute a confidence interval for a difference of two means, given two samples.

Randomized variables: sample raw data and confidence level. 

Adapted from section 7.3.1 in OpenIntro Statistics (4th ed).

This question assesses the learner's ability of calculating confidence intervals for numerical data and conducting a one-sample t-test.

Randomized input values: sample summary statistics and confidence level.

Adapted from question 7.12 in OpenIntro Statistics (4th ed).

Assessment of basic knowledge of confidence intervals; no randomisation.

This question assesses learners' ability to conduct a two sample t-test. 

This question assesses learners' ability to:

- construct a confidence interval for a proportion given corresponding summarised data;

- predict the sample size required to limit the margin of error to a given value.

True/false question type to assess knowledge of basic aspects of ANOVA.

True/false question type to assess knowledge of the basics of linear correlation and regression.

To assess interpretation of a statistical software output and use corresponding equation to make prediction.

Students are supposed to use Excel (or similar) to find the answers (e.g., enter coordinates of two points then plot and add trendline).

Uses an embedded Geogebra graph of a line $y=mx+c$ with random coefficients set by NUMBAS.

Calculate the Pearson correlation coefficient and conduct a hypothesis test.

Conduct a linear regression analysis using a spreadsheet or stats program.

Find a regression equation.

Calculate the z-score and percentile of an observation. The question uses the random person extension.

Assessment of application of different model selection approaches in multiple regression.

True/false question type to assess basic knowledge of confidence intervals.

Multiple response question (3 correct out of 6). Selection of questions from a pool. Real data from a YouGov survey.

This questions assesses the ability to conduct an ANOVA and interpret the results.

Adaptive marking: an error in calculating F can be carried over to the calculation of the p-value as well as the test conclusion.

For practising how to recognise paired data as the first step to identify a suitable statistical analysis (such as the paired t-test or Wilcoxon test).

No description given

Basic properties of atoms

Basic solving of linear equations

Basic solving of linear equations