Unit 1: Introduction to Business Stat & Data Collection

• Statistics came from the Italian word which means statesman

  Statista
• This refers to the body of techniques used for collecting, organizing, analyzing, and interpreting data.

  Statistics
• It means collection of numerical facts or data, such as stock prices, profits, income levels, consumption and the like.

  Statistics
• 2 Division of Statistics

  (1) Descriptive Statistics and (2) Inferential Statistics
• It is concerned with summarizing and describing a body of data in the form of tables, charts, and graphs, and other forms of graphic display which is often done with the use of frequency distribution.

  Descriptive Statistics
• Central tendency, dispersion, shape and association is under what division of statistics?

  Descriptive Statistics
• It is the process of reaching generalization about the whole population by examining a portion (sample)

  Inferential Statistics
• The measured characteristics of a sample are called?

  Sample Statistics
• The measured characteristics of a statistical population, or universe, are called?

  Population Parameters
• The procedure by which the characteristics of all the members of a defined population are measured is called?

  Census
• Deduces properties of a given sample based on known characteristics of the population

  Deductive Statistics
• Facts and figures collected, summarized for presentation, analyzed and interpreted

  Data
• All data collected in a particular study are referred to as?

  Data set
• Entities, can be human or non-human, on which data are collected?

  Element
• Characteristic of interest for the elements?

  Variable
• Set of measurements obtained for a particular element.

  Observation
• Two types of data according to the NATURE OF DATA

  (1) Categorical or Qualitative Data and (2) Numerical or Quantitative Data
• Two types of data under Categorical/Qualitative Data

  (1) Dichotomous and (2) Multinomial
• There are only 2 categories or choices which can be designated as binary for coding purposes

  Dichotomous
• There are 3 or more categories or choices and when coded, zero is refrained from being used.

  Multinomial
• Two types of data under Numerical/Quantitative Data

  (1) Discrete and (2) Continuous
• Countable numbers and whole numbers which cannot be in fraction form

  Discrete
• Numbers which are in fraction forms such as price, income, weight, height, length

  Continuous
• Types of data according to TIME PERIODS & NUMBER OF ELEMENTS

  (1) Cross-sectional

  (2) Time series

  (3) Panel or Longitudinal
• One time period only (current) and many elements

  Cross-sectional
• Many time periods and one element

  Time Series
• Many time periods and many elements

  Panel or Longitudinal
• Types of data according to GROUPING

  (1) Ungrouped Data

  (2) Grouped Data
• Raw data

  Ungrouped Data
• Ranges are made or frequency distribution tables are made

  Grouped Data
• Types of data according to FILING

  (1) Unstacked Data

  (2) Stacked Data
• Cross-sectional or time-series (either horizontal or vertical)

  Unstacked
• Panel or longitudinal (both horizontal and vertical)

  Stacked
• Levels of Measurement Scale

  (1) Nominal Scale

  (2) Ordinal Scale

  (3) Interval Scale

  (4) Ratio Scale
• Consists or uses labels or names to identify an attribute of the element. Labels are of equal status.

  Nominal Scale
• Exhibits property of nominal but the order or rank of the data is meaningful.

  Ordinal Scale
• The data have all the properties of ordinal data and the interval between values is expressed in terms of a fixed unit measurement.

  Interval Scale
• The data in Interval Scale is always numerical. True or False?

  True
• The difference between the values of data in Interval Scale are not meaningful. True or False?

  False
• Data are characterized by not having a meaningful zero value

  Interval Scale