dependent variable in statistics

Probability: Interpreting probability, including long-run relative frequency interpretation 'Law of Large Numbers' concept Addition rule, multiplication rule, conditional probability, and independence Discrete random variables and their probability distributions, including bin..

Estimation (point estimators and confidence intervals): Estimating population parameters and margins of error Properties of point estimators, including unbiasedness and variability Logic of confidence intervals, meaning of confidence level and confidence intervals, and properti..

Consider an example. A person was asked to measure the thickness of a coin. He recorded the following readings: (i) 0.2 cm with ruler (ii) 0.23 cm with vernier (iii) 0.231 cm with micrometer The accuracy of thickness of the coin depended on the instrument used for measuring the thickness..

Quantities such as height, weight, age, amount can have several different values. Quantities which can assume different numerical values are called variables. Variables are of two types: (a) Continuous (b) Discre..

A set of observations is called a called a collection of data. These observations should possess some common characteristics. They are recorded and used for further study. The quantities such as age, height and number of students are called variables..

random variable is a function which associates a real number to each outcome of a random experiment..

A discrete variable can assume only integral values which can be counted. Number of pupils in a school, persons working in a factory are examples of discrete variables. A list of some important terms is given below. (i) ungrouped data (ii) tabulation of data (iii) range (iv) fr..

A random variable which can assume all possible values between certain limits is called a continuous random variable..

random variables which can assume any value over an interval..

Random Variable and Probability Distribution - If is often very important to allocate a numerical value to an outcome of a random experiment. For example consider an experiment of tossing a coin twice and note the number of heads (x) obtained. Outcome : HH HT TH TT No. of heads (x) : 2 1 ..