UNIT 1

• Population


  This refers to a large collection of objects, persons, places, or things. (Denoted by N)
• Qualitative


  These are data that can assume values manifested the concept of attributes.
• Quantitative


  It is defined as the value of data in the form of counts or numbers where each data set has a unique numerical value associated with it.
• Sample


  This can be defined as a subgroup, subset, or representation of a population. (denoted by n)
• Inferential Statistics


  This branch of statistics consists of generalizing samples to populations, performing estimations and hypothesis tests, determining relationships among variables, and making predictions. Deals with the Future.
• Descriptive Statistics


  Deals with the past and present status of the situation. The statistician tries to describe a situation. This involves procedures that are used to summarize, organize, and make sense of a set of scores or observations.
• Descriptive Statistics


  The average age of citizens who voted for the winning

  candidate in the last presidential election.
• Descriptive Statistics


  The variation in the weight of 100 boxes of cereal selected

  from a factory's production line.
• Inferential Statistics


  Hypothesis testing to determine if a new drug is more effective than an existing one.
• Data are facts or sets of information or observations under study.

  Data are gathered by the researcher from a given population or

  get from the sample. Data can be classified into two different

  types: (a) qualitative data and (b) quantitative data.
• Qualitative data is defined as the data that approximates and

  characterizes.
• Quantitative data is defined as the value of data in the form

  of counts or numbers where each data set has a unique

  numerical value associated with it.
• The level of measurement or scale of measure is a classification that

  describes the nature of the information within the values assigned to variables.
• It classifies data into mutually exclusive (non overlapping) categories in which no order or ranking can be imposed on the data.Ex. Gender, Samples, Political Parties

  Nominal
• Ordinal


  classifies data that can be ranked; however, precise differences between the ranks do not exist.

  Ex. Letter Grades (A, B, C, D, F), Small-Medium-Large
• Interval


  It ranks data, and precise differences between units of measure do

  exist; however, there is no meaningful zero.Ex. SAT Scores, Temperature, IQ Test
• Ratio


  Possesses all the characteristics of interval measurement, and there exists a true zero. In addition, true ratios exist when the same

  variable is measured on two different members of the population.Ex. Height, Weight, Age, Number of Items
• Discrete Random Variable


  Its value can be taken in the form of whole numbers.
• Continuous Random Variable


  The values of continuous variables are obtained through

  measuring.
• A probability distribution is a distribution with a set of all possible values of random variable X together with their corresponding associated probabilities.
• A discrete probability distribution (DPD) consists of a discrete random variable together with its corresponding associated probabilities.
• For any discrete random variable “X”

  1. 0 ≤ P(X) ≤ 1

  The probability outcome is between 0 and 1, inclusive.

  2. ∑ P(X) = 1

  The sum of all probabilities is 1.
• Probability Distribution