STS 2

20問 • 1年前

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It is the science of collecting, organizing, summarizing, and analyzing information to draw conclusions or answer questions. It provides procedure in data collection, presentation, organization, and interpretation to have a meaningful idea

Statistics

It basically consists of organizing and summarizing data. This describe data through numerical summaries, tables, and graphs.

Descriptive Statistics

It is the logical process that involves generalizing from a sample to the population from which the sample was selected and assessing the reliability of such generalizations. It is also called as statistical inference or inductive statistics

Inferential Statistics

consists of all the members of the group about which you want to draw a conclusion, while sample is a portion or part of the population of interest selected for analysis

Population

is a numerical index describing a characteristic of a population while a statistic is a numerical index describing a characteristic of a sample.

Parameter

are data that come from an original source, and are intended to answer a specific research question. This can be taken by interview, mail-in questionnaire, survey or experimentation

Primary Data

are data taken from previously recorded data, such as information in previously conducted research, financial statements, business periodicals, and government reports. It can also be taken electronically, for instance via internet websites, etc

Secondary data

is a characteristic of objects, people, or events that does not vary. For example, the temperature at which water boils (100 degree Celsius) is a constant

Constant

is a characteristic of objects, people, or events that can take different values. It can vary in quantity like weight of people, or in quality like hair color of people.

Variable

or categorical variables are variables that yield categorical responses. These are words or codes that represent class or category.

Qualitative variables

or numerical variables are variables that take on numerical values representing an amount or quantity. These numerical values should answer the question how much or how many. − Some examples of qualitative variables are height, weight, distance, salary, etc.

Quantitative variables

or explanatory variables are variables controlled by the experimenter or researcher, and expected to have an effect on the behavior of the subjects.

Independent variables

or outcome variables measure the behavior of subjects and expected to be influenced by the independent variable.

Dependent variables

are quantitative variables that are either a finite number of possible values or a countable number of possible values. These are variables that are countable

Discrete variables

are quantitative variables that have an infinite number of possible values that are not countable. These are variables that are no longer countable but are measurable.

Continuous variables

is the first level of measurement and it is characterized by data that consist of names, labels or categories only. Data cannot be arranged in ordering scheme. Nominal scales have no numerical value.

Nominal Level

involves data that may be arranged in some order, but differences between data values either cannot be determined or meaningless.

Ordinal Level

is a measurement level that specifies the distances between each interval on the scale. Variables of this level have no absolute zero. This means that a value of zero does not mean the absence of the quantity

Interval Level

represents the highest, most precise, level of measurement. Variables of this level have absolute zero which means that a value of zero means the absence of the quantity.

Ratio Level

is the process of gathering and measuring information on variables of interest, in an established systematic fashion that enables one to answer stated research questions, test hypotheses, and evaluate outcomes.

Data collection

HRM: CHAPTER 8

WENDY FEDELIN · 19問 · 1年前

HRM: CHAPTER 8