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Neurosciences year 1 - Statistics in Neuroscience (AM-1216) - summary tests used, and use in SPSS $5.42   Add to cart

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Neurosciences year 1 - Statistics in Neuroscience (AM-1216) - summary tests used, and use in SPSS

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Summary of all statistical tests that are explained in the lecture notes of the course Statistics in Neuroscience (AM-1216) from the master Neuroscience at VU Amsterdam.

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  • January 20, 2022
  • 15
  • 2018/2019
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Statistical Tests
Chi-squared test
χ² test: comparing proportions between groups.
The frequencies for the levels of nominal/ordinal variables can be presented in a contingency
table.




Assumptions:
 Sample is randomly taken from the population assumed under the H0.
 No expected frequencies < 1.
 No more than 20% expected frequencies < 5.

Observed frequencies: the frequencies observed in the sample.

Expected frequencies:
Example blond boy:
marg(a) = total of one group (28)
marg(b) = total of other group (22)
total = total/total (47)




Look up the critical value of under df and α.
If the calculated < critical value  not significant, so H0 is not rejected.
If the calculated > critical value  significant, so H0 is rejected.

In 2x2 tables, the tends to be too large (p-values too small), so a type I error.
Than it is best to use the Yates correction.

Fisher test? P. 723.




1

, Pearson correlation


Is always between -1 and +1.
What is the association strength between variable x and y?
H0: The correlation coefficient is 0.
H1: The correlation coefficient is different from 0.

Assumptions:
 Relation must be linear: can see this by plotting data (x,y).
 Variables are bivariate normally distributed: for each value of x, the values of y are
normally distributed.
 Homescedasticity of variances: the variance does not depend on score.

Analyze  Correlate  Bivariate




To test whether r is significantly different from 0, you have to convert the r into a z-score or t
test statistic, since r does not have a normal distribution.


Look up z-score in the table for normal distribution (small portion  one-sided p-value).

and

Confidence interval of z-score:
 Lower bound: 𝑧𝑟 − (1.96 ∗ 𝑆𝐸𝑧𝑟 )
 Upper bound: 𝑧𝑟 + (1.96 ∗ 𝑆𝐸𝑧𝑟 )
𝑒 2𝑧𝑟 −1
Convert back to confidence interval of r: 𝑟 =
𝑒 2𝑧𝑟 +1



Spearman's rank correlation (rho or rs)
Non-parametric variant of Pearson correlation.


 Lies between -1 and +1
 Rank scores within the variables.
 Calculate the difference between ranks.
o When N>30, than:

and




2

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