Chapter One Impact Report 2023-24 - Flipbook - Page 45
APPENDIX: DATA SOURCES AND METHODOLOGY
Table 1: Total number of reading sessions attended
by group
Median number
of total reading
sessions
attended
Median number of
sessions attended
lasting 15+ minutes
All pupils
25
16
Males
25
15
Females
25
16
Year 1
25
16
Years 1 & 2
25
16
Year 2
25
16
Year 3
24
15
Pupil
premium
25
16
Non-pupil
premium
26
17
Statistical terminology
Statistical Significance (denoted by p values) shows that an effect (e.g.
a difference between groups) exists in a study. If a result is statistically
significant, it is unlikely to have occurred purely due to chance.
A p-value is a measure of the probability that an observed result could
have occurred by chance alone. The lower the p-value, the greater the
statistical significance of the observed difference. Typically, a p-value of
≤ 0.05 indicates that the change was statistically significant. A p-value
higher than 0.05 (> 0.05) is not statistically significant and indicates that
we cannot be confident that this change did not occur due purely to
chance.
Effect size Statistical significance only indicates whether the test result
is not likely due to chance. A statistically significant result does not
necessarily mean that it is practically important. Effect sizes denote the
practical significance of a research outcome. Effect sizes are usually
described as small, medium or large. The larger the effect size, the
greater the practical significance in the real world.
2023-24 Impact Report: Appendix
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