Statistics is used in almost all fields of human endeavor. It’s application in medicine, business, physical and social science is almost limitless. In sports, for example, a statistician may keep records of the number of yards a running back gains during a football game, or the number of hits a baseball player gets in a season. I don’t know whether you have watched the movie Money ball or not. This Movie shows the crucial role of a statistician in success of a baseball team. Furthermore, statistics is used to analyze the results of surveys and as a tool in scientific research to make decisions based on controlled experiments. Other uses of statistics include operations research, quality control, estimation, and prediction. Why Should Students Study Statistics?
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What is Variable?
A variable is a characteristic or attribute that can assume different values.
The following video describes types of variables in statistics. It covers qualitative variables, categorical variables, quantitative variables, discrete variables, and continuous variables.
Independent and Dependent variable
In conducting research, students may be interested in studying the relationships between variables or even predicting one variable from another variable. In these situations, we think of some variables as being the causes of another variable. These variables are called independent and dependent variables. The independent variables can be manipulated or varied, and consequently the dependent variable will vary accordingly. For example we are interested in exploring factors affecting knowledge sharing among graduate students . Based on reviewing literature, several variables such as attitudes towards receiving and giving knowledge and information; Technology Availability; and Perceived Usefulness of Technology (PU)
Measurement
- A measurement or an instrument is used to assign a number to a variable.
- Measurement is the assignment of a number to a characteristic of an object or event, which can be compared with other objects or events. For example, we have three variables which are Membership status, Age, Musical ability. how can we measure these variables?
The measurement level of variables
Nominal Scale
●The lowest scale
● Numbers assigned to identify attributes
● No order/ sequence
( Sex, faculty, phone number, students’ ID number)
Ordinal scale
● The same as a nominal variable but the categories have a logical order
● Arrange from lowest to highest or vice versa
Interval Scale
●Equal intervals on the variable represent equal differences in the property being measured (e.g. the difference between 6 and 8 is equivalent to the difference between 13 and 15)
● Arbitrary Zero
Ratio scale (the highest scale)
● The same as an interval variable, but the ratios of scores on the scale must also make sense (e.g. a score of 16 on an anxiety scale means that the person is, in reality, twice as anxious as someone scoring 8).
● True Zero ( Height, time , volume, and Kelvin temperature)
●The lowest scale
● Numbers assigned to identify attributes
● No order/ sequence
( Sex, faculty, phone number, students’ ID number)
Ordinal scale
● The same as a nominal variable but the categories have a logical order
● Arrange from lowest to highest or vice versa
Interval Scale
●Equal intervals on the variable represent equal differences in the property being measured (e.g. the difference between 6 and 8 is equivalent to the difference between 13 and 15)
● Arbitrary Zero
Ratio scale (the highest scale)
● The same as an interval variable, but the ratios of scores on the scale must also make sense (e.g. a score of 16 on an anxiety scale means that the person is, in reality, twice as anxious as someone scoring 8).
● True Zero ( Height, time , volume, and Kelvin temperature)
Q1. What are the scales of measurement for these variables?
- Program of study
- Speed (km/hr)
- Motivation scores
- Income categories
- Number of SMS received
- Marital status
- Quality of work life scores
- Socio-economic status
- Perception scores
- Membership status
Q2. What are the level of measurement of the following questions?
1. how long ago were you released from the hospital?
2. Which type of unit were you in?
2. Which type of unit were you in?
- Medical unit
- Surgical unit
- Paediatric unit
- Not at all important
- Not very important
- Somewhat important
- Very important
Before beginning your study, you need to decide how you plan to design the study. The research plan refers to the overall strategy that you choose to integrate the different components of the study in a coherent and logical way, thereby, ensuring you will effectively address the research problem; it constitutes the blueprint for the collection, measurement, and analysis of data. Note that your research problem determines the type of design you should use.
Recognizing and identifying the problem is the first step in the research process. A problem may be stated broadly and then systematically restricted through a review of the literature in the initial stages of the research effort. A good statement of the problem should provide the researcher with direction, in pursuing the research. The statement of the research problem should be concise and should identify the key factors ( variables) of the research study.
Recognizing and identifying the problem is the first step in the research process. A problem may be stated broadly and then systematically restricted through a review of the literature in the initial stages of the research effort. A good statement of the problem should provide the researcher with direction, in pursuing the research. The statement of the research problem should be concise and should identify the key factors ( variables) of the research study.
Research Objectives
As you see above, research objectives are written based on statement of problem. Research objectives can be formulated based on three major purposes: Description of phenomenon, Comparison between groups, and Relationship between variables. Based on objectives of your study , hypothesis of the study can be formulated. Moreover, the type of research design (e.g. experiment, survey, observation) and the type of statistical techniques used in the study depend on research objectives.
Choose Appropriate scales and Measures
There are many different ways of collecting ‘data’, depending on the nature of your research ( research objectives, research design: qualitative, quantitative or both). In preparing a questionnaire, you must consider how you intend to use the information; you must know what statistics you intend to use. Depending on the statistical technique you have in mind, you may need to ask the question in a particular way, or provide different response formats.
If you want to conduct quantitative study, there are many thousands of validated scales that can be used in research. Finding the right one for your purpose is sometimes difficult. A thorough review of the literature in your topic area is the first place to start.What measures have been used by other researchers in the area?
In choosing appropriate scales there are two characteristics that you need to be aware of: reliability and validity. Both of these factors can influence the quality of the data you obtain. When reviewing possible scales to use, you should collect information on the reliability and validity of each of the scales. you should also need to pilot-test them with your intended sample. Sometimes scales are reliable with some groups , but are totally unreliable when used with other groups ( change from one culture to another culture).
If you want to conduct quantitative study, there are many thousands of validated scales that can be used in research. Finding the right one for your purpose is sometimes difficult. A thorough review of the literature in your topic area is the first place to start.What measures have been used by other researchers in the area?
In choosing appropriate scales there are two characteristics that you need to be aware of: reliability and validity. Both of these factors can influence the quality of the data you obtain. When reviewing possible scales to use, you should collect information on the reliability and validity of each of the scales. you should also need to pilot-test them with your intended sample. Sometimes scales are reliable with some groups , but are totally unreliable when used with other groups ( change from one culture to another culture).
Reliability
- The reliability of a scale indicates how free it is from random error.—Reliability is the ability of the measure to produce the same results under the same conditions.
- Two frequently used indicators of a scale’s reliability are test-retest reliability and internal consistency.
- The test-retest reliability of a scale is assessed by administering it to the same people on two different occasions, and calculating the correlation between the two scores obtained. High test-retest correlations indicate a more reliable scale.
- Internal consistency can be measured in a number of ways. The most commonly used statistic is Cronbach’s coefficient alpha . This statistic provides an indication of the average correlation among all of the items that make up the scale. Values range from 0 to 1, with higher values indicating greater reliability.
Validity
The validity of a scale refers to the degree to which it measures what it is supposed to measure. The main types of validity are content validity, criterion validity and construct validity.
Measurement error
The degree to which the observed values are not representative of the “true” values
—Sources of measurement errors:
—Sources of measurement errors:
- —Data entry errors
- —Imprecision of the measurement
- —The inability of respondents to accurately provide information
- —Multivariate measurements or summated scales
- —Validity
- —Reliability
when the reliability and validity of the questionnaire are established , data can be collected. Collecting data from the population need great deal of time and energy. It is often costly. Hence, data can be taken from a subset of the population which is called sample.
1.Probability samples or Random samples
A random sample is a probability sample in that every population member has a equal probability of selection. A random sample is an unbiased sample. A random sample is representative of the population from which it was selected.
A random sample is a probability sample in that every population member has a equal probability of selection. A random sample is an unbiased sample. A random sample is representative of the population from which it was selected.
- —Simple random samples
- —Stratified random samples
- —Cluster samples
- —Systematic samples
- —Convenient samples
- —Purposive samples