Please enable JavaScript.
Coggle requires JavaScript to display documents.
Statistical Analysis (Descriptive Statistics (Frequency Distribution:…
Statistical Analysis
Descriptive Statistics
Frequency Distribution
: systematic arrangement of numeric values from low to high
Shape
Symmetry
Positive
Negative
Normal distribution
(bell shaped curve)
Inferential
Shape
symmetric, unimodal, mesokurtic
Standard Deviation
1 SD: 68%
2SD: 95%
3SD:99%
Modality
Unimodal
Bimodal
Multimodal
Peakedness
Leptokurtic
Mesokurtic
Platykurtic
Central Tendency
: common set of scores that comes from the center
Mode: most frequent
Best for nominal measures
Median: middle point
Skewed distribution
Mean: average
Normal distribution
Variability
Indexes of Variability
Standard Deviation:
Average devotion from the mean
Range:
highest value minus lowest value
Degree of Variability
Homogeneity:
alike, leptokurtic
Heterogeneity:
different, great variability, platykurtic
Bivariate
: describing relationship between 2 variables
Contingency Tables (cross tabs)
involves 2 variables crosstabulated
Nominal or ordinal
Correlation Coefficients
Indicates direction and magnitude between 2 variables
Pearsons r (+1 to -1)
Used for interval or ratio level measures
Positive Correlation: same direction
Negative Correlation: opposite direction
Inferential Statistics
Parametric
: estimation of a parameter (interval/ratio)
Independent Variable= nominal
Dependent Variable= ratio/interval
2 groups means
Paired t test
Independent Groups
:
Compares 2 sample means from different populations (men and women) regarding the same variable to determine whether the
difference between
2 means is statistically significant or by chance alone
Dependent Groups
Comapres the means of 2 related groups to determine whether there is a statistically significant difference between these means
3 or more groups means
ANOVA
One Way ANOVA:
tests difference between 3 groups
Multifactor ANOVA:
tests 2 or more independent variables with regard to a variable outcome to test the effect the IV has on that outcome
Repeated Measures ANOVA:
tests the same subjects at the baseline at different points in time
Pearson's r
Variables are interval/ratio
Calculates the Probability that the correlation between two variables is not zero
Correlation Matrix:
multiple variables can display all pairs of correlations
Non parametric
: measurements nominal or ordinal (not normally distributed)
Hypothesis testing??????
Chi-squared
: tests the difference in proportion in categories with contingency tables
Data measured at nominal level
Includes 5 data points (degrees of freedom)
Pearson's r