O1 Understand and apply the language of statistical hypothesis testing, developed through a binomial model, including null hypothesis, alternative hypothesis, significance level, test statistic, one-tail test, two-tail test, critical value, critical region, acceptance region and p-value; extend to correlation coefficients as measures of how close data points lie to a straight line and interpret a given correlation coefficient using a given p-value or critical value, excluding calculation of correlation coefficients.

Quick explanation

O1 Understand and apply the language of statistical hypothesis testing, developed through a binomial model, including null hypothesis, alternative hypothesis, significance level, test statistic, one-tail test, two-tail test, critical value, critical region, acceptance region and p-value; extend to correlation coefficients as measures of how close data points lie to a straight line and interpret a given correlation coefficient using a given p-value or critical value, excluding calculation of correlation coefficients

• This point belongs to Statistics, especially Hypothesis testing language.
• You need to be able to o1 Understand and apply the language of statistical hypothesis testing, developed through a binomial model, including null hypothesis, alternative hypothesis, significance level, test statistic, one-tail test, two-tail test, critical value, critical region, acceptance region and p-value; extend to correlation coefficients as measures of how close data points lie to a straight line and interpret a given correlation coefficient using a given p-value or critical value, excluding calculation of correlation coefficients.
• The key ideas to know are critical region, alternative hypothesis, and significance.
• Use the linked flashcards and practice questions to check recall, then practise applying the idea in an exam-style answer.