Largely
there are two types of data sets
- Categorical or qualitative
- Numeric or quantitative
A categorical data or non numerical data - where variable has value of observations in form of categories, further it can have two types-
a. Nominal b. Ordinal
a.Nominal data has got named categories
e.g. Marital status will be a nominal data as it will get observations in following categories- Unmarried, married, divorced/separated, widowedb.Ordinal data will also take named categories but categories will
have rank.
e.g. Risk of acquiring a hospital based infection will have ordinal data set with categories like High, Medium and Low
Numeric data- where variable takes numerical value. It can again be of two types
a. Discrete b. Continuous
- a. Discrete data has distinct set of values, which are countable and belonging to whole numbers set
e.g. Number of students in the class. This variable can take value from 0 to 100 or more, but it will be countable number.
whereas,
- b. Continuous data has defined range, and value of observation can take any value within that interval. In this case value belongs to set of real number within given interval.
e.g. Height of students in the class first. This variable can take any value between 2.5ft to 4ft
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is a collection of methods for planning experiments, obtaining data, and then organizing, summarizing, presenting, analyzing, interpreting, and drawing conclusions based on the data. | Statistics |
is the complete collection of elements to be studied. | Population |
is a sub-collection of elements drawn from a population. | Sample |
are things that describe a sample’s contents. | Descriptive Statistics |
is making inferences about what sample data may indicate about a population | Inferential Statistics |
data can be separated into different categories distinguished by some non-numerical characteristic. | Qualitative |
data consists of numbers representing counts or measurements. | Quantitative |
data result from either a finite number of possible values or a countable number of possible values. | Discrete |
numerical data results from infinitely many possible values that can be associated with measurement error. | Continuous |
sampling is when members of the population are selected in such a way that each has an equal chance of being selected. | Random |
sampling is when you subdivide the population into at least two different sub-populations that share the same characteristics and then draw a sample from each subgroup. | Stratified |
are numbers that describe a population. | Parameters |
are numbers that describe a sample. | Statistics |
sampling is when you divide the population into sections and randomly select some of those sections, and then choose all the members from the selected sections. | Cluster |
sampling is when you choose some starting point and then select every kth element in the population. | Systematic |
is when the mean is significantly less than the median. | Left Skewed |
is when the mean is significantly greater than the median. | Right Skewed |
asking people their political affiliation State of residence Gender | Nominal |
rating how good a movie is by awarding it one, two, three or four stars Letter grade in a class (A, B, C, D, or F) Size of soft drink ordered at a restaurant (small, medium, large) | Ordinal |
measuring the temperature in Fahrenheit | Interval |
measuring the time it takes to run a race | Ratio |
x with a line over it is known as | Mean |
Sx = (x is only on calculator, standard symbol is "s") | Standard Deviation |
number that appears most often in the set. | Mode |
Med = | Median |
the difference between the highest and lowest values in the set. | Range |
Standard Deviation Squared = | Sample Variance |
Greek sigma x = | Population Deviation |