# Inferential statistics: Foundations

Chapter 11 of Performing Music Research considers the main features of inferential statistics. Statistics describe the characteristics of particular samples and guide the inferences that may be drawn from those characteristics not only to the sample but also the wider population. The use of inferential statistical tests thus enables researchers to make comparisons between studies and draw generalizable conclusions. The chapter begins by showing how the probability that a finding is the result of chance, or random “noise” (fluctuation) in the data, can be quantified. It then considers how to judge the relative size of the finding and the general properties of data.

# Research spotlight

Box 11.2
The satisfaction and stress of singing professionally

Research investigating how singers’ bodies react to the pressures of public performance.

#### Credits

Fancourt D, Aufegger L, & Williamon A (2015), Low-stress and high-stress singing have contrasting effects on glucocorticoid response, Frontiers in Psychology, 6 (1242), 1-5 [DOI].

Film produced by: Tantrwm Digital Media

# Practice questions

These questions test your knowledge of the content of Chapter 11.

Means, medians, and standard deviations are examples of inferential statistics.
The p value describes the likelihood of finding an effect as large as, or larger than, what was observed assuming that...
The probability of a Type I error is represented by the __________ value.
Most research in the social sciences uses a threshold of p < .05 to determine statistical significance.
The statistical power of a test can be increased by using a Bonferroni correction.
A __________ analysis can be used to determine how large a sample would be required to identify a significant effect with a known effect size.
Which value is not a component of a power analysis?
The parametric assumption of homogeneity of ___________ assumes a similar distribution of data in each sample being compared.
A distribution of data that is taller and narrower than a normal distribution is known as what?
Which data transformation are you carrying out when you divide 1 by each value?