RANDOM VARIABLES AND PROBABILITY DISTRIBUTION Flashcards
is any information, characteristics, number or quantity that describes a person, place, thing or idea that can be counted.
Variable
Variables can either be..
Qualitative or quantitative
Quantitative variables can be..
Discrete or continuous
the value is dependent to the outcome of a well-defined random event or experiment (such as throwing a pair of dice).
Random Variable
represents the number of distinct values that can be counted in an event.
Discrete Variable
What kind of quantitative variable is the following?
Number of students in a class, Number of chairs inside the room, No. of patients in the hospital.
Discrete Variable
a quantitative variable that can assume an infinitely many, uncountable no. of real number values.
Continuous Variable
What type of quanti variable are the following?
** The speed of a car, The amount of sugar in a cup of tea.
Sample space- is the set of all possible outcomes in an experiment.**
Continuous
are values that are obtained from functions that
assign a real number to each point of a sample space.
Possible Values of a Random Variable
is a function P(X) that shows the relative probability
that each outcome of an experiment will happen.
Probability Distribution Function
is a probability distribution function of a discrete random
variable. It assigns a probability value to each sample point.
Probability Mass Function
is a table of values that shows the probability of any of
the outcomes of an experiment
Discrete Probability Distribution
is the equivalent value of a raw score expressed in terms of the mean (μ) and standard deviation (σ) of the distribution. It measures the distance of an particular raw score (x) from the mean in standard deviation units.
Standard core - z score
is a measure used in statistics indicating the value below which a give percentage of observations in a group of observations fall.
Percentile
a give percentage of observations in a group of observations fall.
z-score- is an essential component in standard normal distribution.
Percentile
2 types of random variables
Discrete and Continuous
refers to the entire group that is under study or investigation.
Population
a subset taken form a population, either by random or nonrandom sampling techniques.
Sample
the process of selecting a few (a sample) from a bigger group (the sampling population) to become the basis for estimating or predicting a fact, situation, or outcome regarding the bigger group.
Sampling
2 Types of Sampling Tehcniques
Probabilistic and non-probabilistic
depends on chance and likelihood. This implies that all members of the population have equal chances of being chosen to be part of the sample.
Probabilistic
4 types of probabilistic sampling technique
random, stratified-random, systematic, and cluster
defined as a sampling technique in which the researcher selects samples based on the subjective judgment of the researcher rather than random selection.
Non probabilistic
5 types of non-probabilistic sampling
convenience, consecutive, quota, judgmental, and snowball sampling.
subjects are selected by random or lottery. Each member of the population has an equally likely chance of being selected.
Random sample
subjects are selected by random numbers or using the nth number after the first subject is randomly selected from 1 to n.
Systematic Sample
the population is divided into subgroups, so that each population member is in only one subgroup. Here, individuals are chosen randomly from each subgroup.
Stratified - Random Cycle
subjects are selected by using intact groups (cluster) such as a neighborhood or a household that is representative of the population. This is used for large school districts or large geographical areas.
Cluster Sample
researchers look for a specific characteristic in their respondents, and then take a tailored sample that is in proportion to a population of interest.
Quota Sampling
also called purposive sampling or authoritative sampling is a technique in which the sample members are chosen only on the basis of the researcher’s knowledge and judgment.
Judgement Sampling
referral sampling is a technique in which the samples have traits that are rare to find. This is a sampling technique, in which existing subjects provide referrals to recruit samples required for a research study.
snowBall sampling or change
is a number which describes a sample. It can be directly computed and observed. An example of a statistic is the sample mean, which serve as an estimator for the population mean.
Statistic
is a descriptive measure of a population. While a statistic can be directly computed and observed, the value of a parameter can be approximated and is not necessarily equal to the statistic of a sample.
Parameter
is the probability when all possible samples of size n are repeatedly drawn from a population.
Sampling distribution
