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42 Cards in this Set
- Front
- Back
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1) object 2) variable 3) observations |
2) characteristic that assumes different entities 3) different values of a variable measured |
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Raw data |
Unprocessed data |
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Time series data |
A sequence of measurement s collected on the same element for the same variable for different periods |
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Misus of statistics |
Inappropriate method, unrepresentative subgroups to study,inappropiate summarizing.. ect |
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Cross sectional data |
Measurements taken on a group of individuals at the same time |
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Longitudinal data |
Measurements taken on a group of objects at regular intervals of time to provide information about changes |
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Secondary data |
Second hand information . Information collected by someone else |
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Adv s of secondary data |
Time saving Accessibility Saving of money Feasibility of both longitudinal and international comparative studies Generating new insights |
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Dis advs of secondary data |
Inappropriateness of the data Lack of control over data quality Required data may not be available Data may be out of date |
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Advs of primary data |
Targeted issues are addressed Data interpretation is better Recency of data Proprietary issues Data is away safe from competitors |
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Disadvantages of primary data |
High cost Time consuming Inaccurate feed backs(bias) More number of resources required |
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What are the types of variables? |
Quantitative(discrete and continuous) Qualitative(nominal and ordinal) |
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Define quantitative |
Are variables that yield measurable values or scores and frequencies. # expressed numerically |
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Define qualitative |
These are descriptive in nature |
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Discrete variable |
Characteristic of an object that can take only countable values or exact fixed values . |
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Continuous variable |
Variables that assume any value within an interval or take values that are not countable eg weight , age |
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Nominal scale |
A variable whose possible values are categorized |
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Ordinal scale |
Consists of rank order categories |
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Interval scale |
Natural ordering eg temperature in °c |
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Ratio scale |
Difference between meaningful successive values |
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Must remember |
Frequency distribution is mostly used for quantitative data and less for qualitative data |
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Adv and dis of frequency distribution |
Adv -quick visual picture Dis- identity of observations is lost and are not sure of actual values |
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Define frequency |
Number of times a certain value occures |
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How to construct class boundaries? |
Obtained by taking the average of the upper class limit of one class and the lower class limit of the next higher class. |
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What is class width /size? |
Using class boundaries |
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Define array |
Arrangement of data in order of size |
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What is the class mark? |
Also known as class mid point. This is done by adding the class limit s/boundaries and dividing by 2. |
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Define adjacent |
Side by side |
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How to construct a frequency distribution / table ? |
STEP 1: identify the largest and smallest number STEP 2: calculate the range STEP 3:k=1+3.322=number of classes STEP 4: range /k= class size STEP 5: decide where to start the first class *(must contain smallest observation) |
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Relative frequency |
Frequency/total frequency |
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Less than cumulative frequency |
The number of observations lower than the upper class boundary * Usually starts with the first classes upper boundary |
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More than cumulative frequency |
*usually starts with the first classes lower boundary |
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Histogram |
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Bar chart Bar chart |
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Frequency polygon( graphical representation of data) |
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Always to remember about graphs |
Frequency is always vertical and measurements are horizontal. |
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Pie chart |
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Stem and leaf |
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Arithmetic mean |
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Mean:ungrouped arithmetic and grouped |
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Harmonic , geometric, weighted mean and combined |
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Median grouped and ungrouped |
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