BSNS 112 Exam Preparation Questions And Correct Answers, Complete Verified Solution.
Descriptive statistics
- methods of organising, summarising and presenting data in a good form
e.g. graphs, tables, measures
Inferential statistics
Random sample of data taken from a population to describe a...
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BSNS 112 Exam Preparation Questions And Correct
Answers, Complete Verified Solution.
Descriptive statistics
- methods of organising, summarising and presenting data in a good form
e.g. graphs, tables, measures
Inferential statistics
Random sample of data taken from a population to describe and make inferences about
the population
Types of data
quantitative and qualitative
Quantitative data
Numerical
e.g. Age in years
Qualitative data
Grouped or categorical
e.g. S, M, L, XL, XXL
Categorical data (Qualitative)
Nominal or Ordinal
Numerical data (Quantitative)
Discrete or Continuous
Frequency
x
Proportion
p
Mean
average
Median
middle number
Mode
most common number
Trimmed mode
most common number with extreme 5% trimmed
Central locations
Mean
Median
Mode
Trimmed Mode
Measures of spread
Range
Interquartile range
Variance
Range
Max observation less Minimum
, IQR
Middle 50%
Variance
Squared deviation around the mean
Standard Deviation (SD)
average distance observations are away from the mean
Coefficient of variation
no units = good for comparisons
relative measure of variability
used to compare variability between groups with different means
Box and whisker
Sample variance
Standard Deviation Equation
Coefficient of variation equation
Measure of shape
Skewness and Kurtosis
Skewness
A skewness value more than twice its std. error is taken to indicate significant departure
from symmetry
around 0 = symmetrical
Positively skewed
Negatively skewed
Symmetrical
Skewness Rule
2x std error = significantly positively skewed
Kurtosis
extent to which observations cluster around a central point and fatness of tails
Normal Distribution Kurtosis
0 Kurtosis
Positive kurtosis
data clusters more in centre with long tails
Negative Kurtosis
data is less clustered with shorter tails
Kurtosis Rule
kurtosis/kurtosis error is >2 = significant positive kurtosis
Population
Whole collection of things under consideration
Sample
Proportion of population
Parameter
Describes a characteristic of a population
Population mean
m
Sample mean
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