Random variables
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This document discusses discrete and continuous random variables. It defines a random variable as a numerical value that describes the outcomes of a chance process. Discrete random variables can be counted, like the number of coins in your pocket, while continuous variables cannot be counted and take on any value within a range, like age which can have fractional values. The document provides examples of discrete variables like the number of books owned and continuous variables like temperature. It concludes that a variable is discrete if it can be counted, and continuous if it can take any value between two points.
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This document defines and describes different types of variables that are commonly used in research. It begins by explaining that observations or participants can have characteristics that are either constants (the same for all) or variables (differ between participants). The main types of variables discussed are independent variables (factors being studied for their effects) and dependent variables (outcomes being measured). Other variable types covered include moderator variables, quantitative vs qualitative variables, and continuous vs discontinuous variables. Demographic variables are also defined as characteristics used to describe research samples.
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Random variables
- 2. VARIABLES 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, business income and expenses, country of birth, capital expenditure, class grades, eye colour and vehicle type are examples of variables. It is called a variable because the value may vary between data units in a population, and may change in value over time.
- 3. RANDOM VARIABLES A random variable takes numerical values that describe the outcomes of some chance process. Two main types of random variables: 1. Discrete random variables 2. Continuous random variables
- 4. DISCRETE RANDOM VARIABLE Discrete variables are countable in a finite amount of time. For example, you can count the change in your pocket. You can count the money in your bank account. You could also count the amount of money in everyone’s bank accounts. It might take you a long time to count that last item, but the point is—it’s still countable.
- 5. CONTINUOUS RANDOM VARIABLE Continuous Variables would take forever to count. In fact, you would get to “forever” and never finish counting them. For example, take age. You can’t count “age”. Why not? Because it would literally take forever. For example, you could be: 25 years, 10 months, 2 days, 5 hours, 4 seconds, 4 milliseconds, 8 nanoseconds, 99 picosends…and so on.
- 6. To sum up … If a variable can take on any value between two specified values, it is called a continuous variable; otherwise, it is called a discrete variable.
- 7. AM I DISCRETE OR CONTINUOUS ?? 1. If you start counting now and never, ever, ever finish (i.e. the numbers go on and on until infinity), you have what’s called a variable.
- 8. AM I DISCRETE OR CONTINUOUS ?? If your variable is “Number of Planets around a star,” then you can count all of the numbers out. That is a variable.
- 9. The number of desks in the room The average weight of all students Number students in a class Number of shoes you have Number of books you have Temperature in degree Celsius Time spent in studying Time (nearest hours) spent in studying AM I DISCRETE OR CONTINUOUS ??
- 10. ACTIVITY 1 Discrete vs.Continuous November 7, 2019 Directions: Determine if the following set of data is discrete or continuous. 1.The heights of your classmates. 2.The number of books on your shelves. 3.The weights of watermelons. 4.The age of a person. 5.The number of words in a book.
- 11. ACTIVITY 1 Discrete vs.Continuous November 7, 2019 Directions: Determine if the following set of data is discrete or continuous. 6. number of heads when flipping three coins 7. time it takes to get to school 8. distance traveled between classes 9. students’ grade level 10. number of students present