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What is Data? What are the different types of data? What is quantitative and qualitative data? What is the variable in statistics? What are the types of variables? What's Quantitative Data? What is the difference between discrete data and continuous data? What is a numerical variable? Multiple Choice Quiz |
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What is Data? Data is a collection of facts, such as numbers, words, measurements, observations or even just descriptions of things. Types of Statistical Data: Numerical, Categorical, and Ordinal What are the different types of data? It is useful to distinguish between two broad types of variables: qualitative and quantitative (or numeric). Each is broken down into two sub-types: qualitative data can be ordinal or nominal, and numeric data can be discrete (often, integer) or continuous. What are quantitative and qualitative data? Quantitative data are measures of values or counts and are expressed as numbers. Quantitative data are data about numeric variables (e.g. how many; how much; or how often). Qualitative data are measures of 'types' and may be represented by a name, symbol, or a number code. Qualitative data are data about categorical variables (e.g. what type). Quantitative = Quantity Qualitative = Quality Why are quantitative and qualitative data important?
Merging Qualitative and Quantitative Data in Mixed Methods Research: How To and Why Not What are people searching for? (keywords/labels, file type) Where are people conducting their searches? (location, Web search, site search) When are people conducting searches? (date, time) How are people searching? (desktop/tablet/mobile, query/browse/ask) Why are people conducting searches? (goals, intention, motivation) What is the variable in statistics? A variable is any characteristics, number, or quantity that can be measured or counted. A variable may also be called a data item. Age, sex, class grades and eye color are examples of variables. What are the types of variables? There are different ways variables can be described according to the ways they can be studied, measured, and presented. Numeric variables have values that describe a measurable quantity as a number, like 'how many' or 'how much'. Therefore numeric variables are quantitative variables. Numeric variables may be further described as either continuous or discrete: •A continuous variable is a numeric variable. Observations can take any value between a certain set of real numbers. The value given to an observation for a continuous variable can include values as small as the instrument of measurement allows. Examples of continuous variables include height, time, age, and temperature. •A discrete variable is a numeric variable. Observations can take a value based on a count from a set of distinct whole values. A discrete variable cannot take the value of a fraction between one value and the next closest value. Examples of discrete variables include the number of registered cars, number of business locations, and number of children in a family, all of of which measured as whole units (i.e. 1, 2, 3 cars). The data collected for a numeric variable are quantitative data. Categorical variables have values that describe a 'quality' or 'characteristic' of a data unit, like 'what type' or 'which category'. Categorical variables fall into mutually exclusive (in one category or in another) and exhaustive (include all possible options) categories. Therefore, categorical variables are qualitative variables and tend to be represented by a non-numeric value. Categorical variables may be further described as ordinal or nominal: •An ordinal variable is a categorical variable. Observations can take a value that can be logically ordered or ranked. The categories associated with ordinal variables can be ranked higher or lower than another, but do not necessarily establish a numeric difference between each category. Examples of ordinal categorical variables include academic grades (i.e. A, B, C), clothing size (i.e. small, medium, large, extra large) and attitudes (i.e. strongly agree, agree, disagree, strongly disagree). •A nominal variable is a categorical variable. Observations can take a value that is not able to be organised in a logical sequence. Examples of nominal categorical variables include sex, business type, eye colour, religion and brand. The data collected for a categorical variable are qualitative data. Types of variables flowchart:  Data are measurements or observations that are collected as a source of information. There are a variety of different types of data, and different ways to represent data. A data unit is one entity (such as a person or business) in the population being studied, about which data are collected. A data unit is also referred to as a unit record or record. A data item is a characteristic (or attribute) of a data unit which is measured or counted, such as height, country of birth, or income. A data item is also referred to as a variable because the characteristic may vary between data units, and may vary over time. An observation is an occurrence of a specific data item that is recorded about a data unit. It may also be referred to as datum, which is the singular form of data. An observation may be numeric or non-numeric (categorical). For example, 173 is a numeric observation of the data item 'height (cm)', whereas 'Australia' is a non-numeric (categorical) observation of the data item 'country of birth'. A dataset is a complete collection of all observations. What's Quantitative Data? Quantitative data is data that can be measured numerically. Things that can be measured precisely -- rather than through interpretation -- such as the number of attendees at an event, the temperature in a given location, or a person's height in inches can be considered quantitative data. Its foil -- qualitative data -- requires a subjective decision in order to be categorized or measured. What is the difference between discrete data and continuous data? Discrete data can only take certain values (like whole numbers). Continuous data can take any value (within a range). Discrete and Continuous Data Data can be Descriptive (like "high" or "fast") or Numerical (numbers). And Numerical Data can be Discrete or Continuous: Discrete data is counted, Continuous data is measured Discrete Data Discrete Data can only take certain values. Example: the number of students in a class (you can't have half a student). Example: the results of rolling 2 dice: can only have the values 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 and 12 Continuous Data Tape Measure Continuous Data can take any value (within a range) Examples: •A person's height: could be any value (within the range of human heights), not just certain fixed heights, •Time in a race: you could even measure it to fractions of a second, •A dog's weight, •The length of a leaf, •Lots more! What is a numerical variable? The values of a numerical variable are numbers. They can be further classified into discrete and continuous variables. A variable whose values are whole numbers (counts) is called discrete. Multiple Choice Quiz Question 1 Data (High School Statistics, Easy) Which one of the following is quantitative data? A She is black and white. B She has two ears. C She has long hair. D She has a long tail. Quantitative data is numerical information (numbers). The only one that is quantitative is B - two ears. Which one of the following is continuous data? A She has two eyes. B She has five kittens. C She weighs 5.4 kg. D She has four paws. C She weighs 5.4 kg. Discrete data can only take certain values (like whole numbers). Continuous data can take any value (within a range). The weight of a cat is continuous because it can take any value witin certain limits. Which one of the following is discrete data? A She is 45.2 cm long. B She is 22.3 cm high. C She weighs 5.4 kg. D She has 30 teeth. Correct: D She has 30 teeth. A census collects information about: A All members of the population. B All adult members of the population. C A large sample of the population. D A small sample of the population. A Census is when you collect data for every member of the group (the whole "population"). A All members of the population. Which one of the following is NOT quantitative data? A The snake is 7 feet long B The snake has two eyes C The snake is green and yellow D The snake has no legs C The snake is green and yellow The snake is green and yellow is qualitative because it is descriptive. The other three are all quantitative because they tell us about quantity. Even D tells us that the number of legs is zero, so is quantitative. Which one of the following is discrete data? A Sam is 160 cm tall B Sam has two brothers and one sister C Sam weighs 60 kg D Sam ran 100 meters in 10.2 seconds B Sam has two brothers and one sister Discrete data can only take certain values (like whole numbers) Continuous data can take any value (within a range) B is discrete because the numbers of brothers and sisters can only be values like 0, 1, 2 etc... The other three are all continuous because they can take any value within a range, such as 160.3 cm or 75.35 kg. A sample collects information about: A All members of the population. B All adult members of the population. C None of the population. D Some, but not all, of the population. A Sample is when you collect data just for selected members of the group. This can be some, but not all, of the population. D Some, but not all, of the population. |
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