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Wilcoxxin
________ signed test: nonparametric alternative to t- test for correlated samples.
Inferential statistics
________- processes for drawing conclusions about a population based on data.
Confidence interval
________ and level: range of values observed in sample that accurately reflects the population.
Nonsymmetric
________: either positively (point towards the left) or negatively (point towards the right) skewed.
Kappa
________: determine the degree of agreement between two or more judges.
Correlational analysis
________: determines relationships among variables.
error
Sampling ________: sample not representative of population.
Normal distribution
________: both halves are identical.
Kurtosis
________: distribution characterised by its shape.
linear relationship
Pearson: measures the strength and direction of a(n) ________ between the x and y variables.
descriptive statistics
Bivariate ________: contingency tables and correlational analysis.
Statistical analysis
________: Organisation and interpretation of data according to well defined, systematic, and mathematical procedures and rules.
null hypothesis
Type I error (alpha): researcher fails to accept ________.
Non parametric
________ statistics: test hypothesis when the data violates one or more of the assumptions of parametric procedures.
Parametric statics
________: formulas that test hypothesises based on three assumptions.
Alternate hypothesis
________: definite difference between groups of a subject.
T test
________: Compare the difference of means of one variable.
Error variance
________: researcher overlooks unexpected problems in test environment.
Level of significance
________: statement of the expected degree of accuracy of the findings based on sample size.
Systematic variance
________: researcher fails to control extraneous variables such as age, race, gender.
Descriptive statistics types
________: MCT, measures of variability, bivariate descriptive statistics.
Hawthorne effect
________: attention given to subjects increases positive outcome.
Inferential statistics
________: inferences to known population.
Null hypothesis
________: statement of no difference.
Null hypothesis
statement of no difference
Alternate hypothesis
definite difference between groups of a subject
Statistical analysis
Organisation and interpretation of data according to well defined, systematic, and mathematical procedures and rules
Levels of statistical analysis
descriptive stats, inferential stats, associational stats, difference
Descriptive statics
data reduction
Inferential statistics
inferences to known population
Associational statistics
causality
Difference
difference between two or more groups of data
Descriptive statistics types
MCT, measures of variability, bivariate descriptive statistics
Measures of central tendency
mode, median, mean
Measures of variability
range, IQR, sum of squares, variance, standard deviation
Bivariate descriptive statistics
contingency tables and correlational analysis
Normal distribution
both halves are identical
Nonsymmetric
either positively (point towards the left) or negatively (point towards the right) skewed
Kurtosis
distribution characterised by its shape
Correlational analysis
determines relationships among variables
Level of significance
statement of the expected degree of accuracy of the findings based on sample size
inferential statistics
processes for drawing conclusions about a population based on data
confidence interval and level
range of values observed in sample that accurately reflects the population
significance level
indicates whether the samples being tests are from the same or different population
one-tailed and two-tailed level of significance
two extreme scores of the bell curve
type I error (alpha)
researcher fails to accept null hypothesis
type II error (beta)
accepts null hypothesis when it should be rejected
parametric statics
formulas that test hypothesises based on three assumptions
parametric stats assumptions
sample is serviced from population with a normal distribution, variance if homogeneous, data measures at interval level
t-test
Compare the difference of means of one variable
one-way analysis of variance (ANOVA)
Test the difference between the means of two or more variables
pearson
measures the strength and direction of a linear relationship between the x and y variables
non-parametric statistics
test hypothesis when the data violates one or more of the assumptions of parametric procedures
chi-squared test
when data is nominal, and computation of mean is not possible
mann-whitney test
test differences between two independent groups
Wilcoxxin signed test
nonparametric alternative to t-test for correlated samples
Kruskal-wallis test
non-parametric alternative to ANOVA
Kappa
determine the degree of agreement between two or more judges
Hawthorne effect
attention given to subjects increases positive outcome
Placebo effect
receiving treatment may produce positive expectations
Honeymoon effect
a short-term effect of a new treatment procedure subjects hope will impact on the disease
Research bias
researcher affecting results through enthusiasm and interest for the treatment to be effective
Test administer bias
person aware which subjects get treatment and which dont
Sampling error
sample not representative of population
Systematic variance
researcher fails to control extraneous variables such as age, race, gender
Error variance
researcher overlooks unexpected problems in test environment
Note 
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