Stats flashcards

Questão	Responda
(dependent variables) define: nominal, ordinal, interval, ratio.	Nominal- categorical (type of beer). Ordinal- relative position (rank of beer). Interval- difference between 2 values meaningful(mean temp of beer). Ratio- similar interval w/ meaningful zero point(beers per night).
Define within-subjects and between-subjects designs.	Within subjects(repeated measures), group experience both conditions. Between-subjects, 2 groups experience one condition.
3 measures of central tendency	Mean. Mode and Mediun.
Define standard deviation and variance? (And why?)	variance = sum of squares / number of items standard deviation brings variance back to original measures (not squared :P) Variance = (Std Deviation)^2 the deviation of individual samples can be positive or negative, by simply adding them together they would cancel each-other out, by squaring the std deviation it truly represents the total variance.
Normal Distribution	A function the represents the distribution of many random variables as a symmetrical bell-shaped graph.
What is a Gaussian equation?	An equation to find the height of the distribution at any point:
Define a positive-skew, negative-skew (and un-skewed)	Image: 4da0382a-9891-4417-8367-b6a3b10393be (image/jpg)
What are Z-scores? (and how are they calculated?)	They tell us how many standard deviations are above/below the mean value. calculated by taking the observation, subtracting it from the mean of all observations, and dividing the result by the standard deviation of all observations. by converting a distribution of observations into Z-scores a new distribution is created that has a mean of 0, and a standard deviation of 1.
How to determine sampling error.	if you take a random sample from population of values to estimate parameters of original population. BUT the mean of each sample will differ from the true mean of the population.
Standard Error of the Mean (SEM) - also called the 'confidence interval'	essentially a measure of how confident we are that we know the true population mean, this is dependent on: variability of original data, number data used to create sample mean. -standard deviation squared (negative results become positive) -tells you the RANGE of values the mean might really take.
standard deviation vs SEM	stdev=the amount that scores vary. SEM=measure of confidence we know true population mean.
An easy example to explain degrees of freedom?	if we keep alternating males + females around a table then (N-2) can choose their own seat.
Define 'co-variance'	How much 2 random variables change TOGETHER. If the 2 variables show very similar patterns the co-variance value will be positive, if they are very different the value is negative .
Explain Spearman's rs	A (Non-parametric) bivariate correlation coefficient (uses ORDINAL data) that relates to Pearsons Rho, first work out the ranking of the data then perform pearson's Rho(r^2) on the rank scores. *ranking the data reduces the impact of outliers
Partial Correlations?	sometimes a correlation between 2 variables might only be explained by another variable e.g. does excessive drinking affect the brain during exams? -correlate how many times one gets drunk(A) with exam score (B) -what about the fact that the drinking stopped one from being at home studying? (C)
Correlation terminology: -Partialled out? -Zero order correlation -first-order corr -second-order corr	-Variable C is referred to as being 'partialled out'/held constant -A simple correlation is also called a zero-order correlation. -first order has one variable held constant -second order has two variables held constant
What is 'power'?	- the ability of a test to detect an effect, it can be used to determine how big a sample is required to detect a significant effect. P= the probability of finding an effect given that one truly exists. (Ho is false) denoted by 1-'Beta'
What does the Bonferroni correction do?	divides the alpha value by the number of statistical comparisons made to see how many tests will give false results.
What to do if there are low assumptions for data in a chi-square test?	'collapse categories' and include smaller categories within other categories- or discard a small category and run the test on the remaining data.
What is a 'binomial test '?	used for data that can only have 2 values, compares whether frequency of occurrence for 2 values has some expected ratio e.g. whether a coin is giving heads suspiciously often or within the range expected by chance.
What does an ANOVA do?	compares multiple groups (as using multiple t-tests would require an abnormally low alpha) compares the amount of variance explained by the experiment with variance that is unexplained.
For an ANOVA what is 'F'?	F is the explained variance divided by the unexplained variance
A repeated measures ANOVA?	parametric test that establishes the differences between multiple groups in a repeated measures design
What is regression analysis?	a technique to fit a model (mathematical equation) to data, can be a very simple or complex (few or many parameters). Simplest non-trivial model is the linear model (y=a+bx) (equation of a line). **Once the equation has been fitted to the data the slope of the relationship between 2 variables becomes clear and it is much easier to predict y given x etc.
regression analysis versus correlations?	-correlations show that there is a relationship between the variables and how much noise contributes -regression analysis tells us what the relationship is but does NOT tell us whether it is real.
Define Non-Parametric tests	where the data is not required to fit a normal distribution- this (usually) uses ordinal data so does not rely on numbers, but rather a ranking or order of sorts. -parametric= preferred because more 'power'
What do resampling techniques do?	measure sampling error by repeating the sampling process a large number of times. This can determine the likely error introduced by sampling by looking at the variability in the resampling.
Between-subject randomisation tests (aka permutation tests)	want to determine the likelihood of getting differences this extreme if the data all came from a single population. Simulate running the experiment many times, with data all coming from 1 population to check what range is normal. Keep measured values but SHUFFLE them (randomly assign them to 2 groups)- count how often the difference between the new means is bigger than between the measured means. Assume they are real and sensible values (do not assume anything about distribution).
Within-subjects randomisation test	in each group resample the values and shuffle for each subject rather than across the whole data set (randomise the sign of the difference for each pair)
Bootstrap resamples	can be used to calculate: confidence interval of a mean or SEM etc. Can also determine whether some test values are inside or outside the 95% confidence interval (is a non-parametric method so makes very few assumptions of the data).
A one-sample test (resampling stats)	we can simply count how often a mean occurs within the bootstraps, order the data find how many values are </> the mean.
Jack knife method (resampling stats)	similar to bootstrap but rather than 'randomly sampling with replacement', resampling is done by 'selecting all data but one'.
Monte-carlo method (resampling stats)	create data based on model stimulations & compare these to real data..
Perentile bootstrap confidence interval	order bootstrap samples and trim the top and bottom 2.5% to create 95% confidence- see where the data lies.
Describe error-bar plots	indicate the variability or confidence interval for a data point. Should be added whenever you display a mean of several measurements. Std-dev, SEM or CIS can all be used to make the error bars.
Describe a Kruskal-Wallis test	Non-parametric test that establishes the differences between multiple groups with one independent variable in an independent measures design.
Describe Wilcoxen signed-rank test	a non-parametric test that establishes the differences between 2 conditions that are experienced by 1 group.
Describe a Friedman's ANOVA	Non-parametric test that establishes the differences between multiple groups in a repeated measures design.
What does a significant test statistic tell you?	that there is an effect in the population of sufficient magnitude to be scientifically interesting.
Define Platykurtic and Leptokurtic distributions	-Platykurtic distributions are shorter and flatter -Leptokurtic distributions are taller and 'peakier'
Type 1 error definition and relation between power & alpha	falsely accepting the exp hypothesis (false alarm) probability = alpha (probability that this occurred by chance is 0.05, probability of data must be less than alpha...)
In SPSS what is the correct way to record non-numerical values?	to define the variable as "string".
What does a Chi-Square test do?	compares the frequencies observed in certain categories to the frequencies you might expect to get in those categories by chance using a contingency table.
Describe a Chi-square good-ness of fit test	uses one categorical variable from a single population
Describe a Pearson's Chi-square test	EXAMPLE: - you are asking adults which fizzy drink they prefer: Pepsi or Sprite, and comparing the answers given by each gender.
Describe an independent samples t-test	parametric test that establishes whether two means collected from independent samples differ significantly.
Describe a related-sample t-test	parametric test that establishes the differences between 2 conditions that are experienced by 1 group.
Describe a One-way ANOVA:	Parametric test that establishes the differences between multiple groups with one independent variable in an independent measures design.
Describe a factorial ANOVA	a test that establishes the differences between multiple groups using multiple independent variables.
What are post-hoc tests?	set of comparisons between group means that were not thought of before data were collected. Typically involve comparing the means of all combinations of pairs of groups. *less power than planned contrasts & are usually for exploratory work for which no firm hypotheses were available on which to base planned contrasts.
What is a residual?	The difference between the observed value of the dependent variable and the predicted value
Describe heteroscedasticity and homoscedasticity	- hetero= circumstance in which the variability of a variable is unequal across the range of values of a second variable that predicts it. - homo= circumstance in which the variability of a variable is equal across the range of values of a second variable that predicts it.
What does a test of homoscedasticity of error terms determine?	whether a regression model's ability to predict a DV is consistent across all values of the DV.
what does an assumption of homogeneity and heterogeneity of variance mean?	*same as tests of homo/hetero-scedasticity but for an ANOVA.
Describe Levene's test:	a test of homogeneity for multiple groups (with independent ANOVA). A significant result implies that the variances are DIFFERENT. *when sample sizes are large, small differences in group variances can produce a significant Levene’s test.
Describe the assumption of sphericity	the assumption of equal variance between multiple variables and multiple groups (ANOVA)
What is standardisation?	the process of converting a variable into a standard unit of measurement. The unit of measurement typically used is 'standard deviation unit' (z-scores). *allows us to compare data when different units of measurement have been used.
How much variance is explained by a correlation? (e.g. 0.9)	the percentage of variance that is explained is equal to the square of the correlation coefficient (e.g. 0.81)
Why mustn't the expected values of a chi-square fall below 5(ish)?	if the individual values are low the category totals are likely to overlap. *need a more specific/sensitive test.
Supposedly how should you compensate for heterogeneity of variance in an independent samples t-test?	by correcting the degrees of freedom.
in a factorial design with 2 factors, if the effect of one factor appears to depend on the levels of the second factor this is called:	an interaction effect.
an experiment was conducted in which participants were given lists to learn in either quiet or noisy environments. Later, recall was either in the same or a different context of learning. What design is this experiment?	Two factorial (2 IV factors) fully independent measures (both are between-subjects).
In linear regression the variable that is being predicted (y) is called:	dependent variable criterion variable
How to calculate the Total Error/Sum of Squares	Square the deviations of the mean (result-mean) and add them together, need to square them so positive + negative don't just cancel each other out! divide by number of items=Variance!
How to calculate the expected frequency off of a contingency table: *for example frequency of men that prefer sport (both genders and several favourite tv shows)	(number of men/total people) X (number of people that like sport/Total) XX the Total
Define: Mean Square Distribution-free-tests *B/b (not Beta)	a sum of squares divided by its degrees of freedom. Non-parametric tests! *the gradient of the regression line and the strength of the relationship between a predictor and the outcome variable.
What is the non-parametric equivalent of the Bonferroni post-hoc tests?	The Games-Howell post-hoc tests. *'no variances assumed'

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	Criado por Rachael Jones quase 9 anos atrás