# Statistical Analysis Test 1 Definitions

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1. Population
The collection of all objects or elements of interest in a study
2. Parameter
A quantitative measure that describes a characteristic of a population
3. Statistic
A quantitative measure that describes a characteristic of a sample
4. Sample
Any portion of a population selected for study
5. Random sample
When each and every element in the population gets an equal chance of being selected in the sample
6. Sampling Units
Non-overlapping collections of elements from a population that covers the entire population
7. Variable
A characteristic observed on sample units that can vary from unit to unit
8. Quantitative Variable
A variable that can be measured numerically
9. Qualitative Variable
A variable that can not assume a numerical value, but can be classified into two or more categories
10. Discrete Variable
A variable that can assume integral values (counting numbers)
11. Continuous Random Variable
A variable that can assume any numberical value over a certain interval(s)
12. The Mean
Suppose we have a data set of sample of n-observations, say x1, x2,x3, , xn. The sample mean is denoted by x̄ and defined as x̄=
13. The Median
The middle number when the measurements of the data set are arranged in order from least to greatest in magnitude (a Ranked data set)
14. The Mode
The value(s) which occur most in a data set
15. Quartile
There are 3 quartiles, namely Q1, Qand Q3 which split the data set into 4 equal parts when the given data set has been ranked
16. Percentile
The kth percentile of a data set is denoted by Pk and defined as the value such that k% of the observations in the data set are less than or equal to that value or equivalently, (100-k)% of observations are greater than or equal to that value.
17. Percentile Rank of Observation
The percentage of values in the data set smaller than this value (≠)
18. Range
The difference between the smallest value and the largest value in the data set
19. Sample Variance (s2)
Suppose we have a sample of n observations, say x1, x2,x3, , xn. The sample variance is denoted by s2 and defined as the sum of the squares of the deviations of the observations in the sample from their mean.
20. Coefficient of Variation
Sometimes we need to compare the variability of 2 data sets that have different units of measurement
21. Classification
forming non-overlapping classes or intervals into which all the observations in the given data set are placed
22. Class Limits
The end points of each class or interval are called the class limits. The lower endpoint of the class is called the lower limit of the class, and the upper endpoint of the class is called the upper limit of the class.
23. Class mark
The midpoint of each class is the class mark. Therefore class mark = of the class. The class mark for the ith class is denoted by xi (book uses mi )
24. Class Frequency
The number of observations falling into a class. The class frequency of the ith class is denoted by fi. The sum of all the class frequencies is equal to the number of observations in the data set.
25. Relative Frequency
The relative frequency of the ith class is denoted by Pi and defined as Pi= , where fi is the frequency of the ith class and n is the sum of all the frequencies.
26. Set
A collection of well-defined objects called the elements of the set. We usually use a capital letter and curly brackets {} to denote a set.
27. Subset
Any part of another set is called a subset. If B is a subset of A, we write as B ⊆ A, that is whatever is in B must be in A.
28. Empty set
is denoted by ф and contains no elements in it
29. Experiement
a process by which an observation is obtained
30. Event
a specific collection of one or more outcome(s) of an experiment
31. Simple Event
An event that can't be decomposed any further
32. Compound Event
An event that can be decomposed into two or more simple events
33. Sample Size
The set of all outcomes of an experiment and is denoted by S.
34. Probability of an Event
The probability associated with an event A defined over the sample space S is denoted by P(A) and defined as P(A) =
35. Union of Events
Let A and B be any two events defined over the sample space S. The union of A and B is denoted by A∪B and defined as the set of all outcomes that are either in A or in B or in both A and B
36. Intersection of Events
• Let A and B be any two events defined over the sample space S. The intersection
• of A and B is denoted by A∩B and defined as the set of all outcomes
• which are in A and B (ie, common in A and B)
37. Mutually Exclusive (or disjointed) Events
Two events A an dB defined over the sample space S is said to be mutually exclusive if A∩B=ф. A∩B=ф implies that P(A∩B)=0
38. Independent Events
Two events A an dB defined over the sample space S is said to be independent events if A∩B=P(A)*P(B. In the case of two independent events, the occurrence of one event does not change the probability of the other.
39. The Complement
The complement of event A is denoted by A-bar and defined as those outcomes in the sample space S which are not in A.
 Author: Jamie_Bee ID: 275010 Card Set: Statistical Analysis Test 1 Definitions Updated: 2014-05-22 02:25:02 Tags: Stats Definitions University Folders: Description: Definitions for Statistical Analysis Show Answers: