RESEARCH Chief characteristics • Due to the nature of the classification variable (i.e.‚ a subject variable)‚ extraneous variables affecting the classification variable cannot be controlled; • However‚ extraneous variables affecting the measurement of the criterion variable can usually be controlled‚ although this may not be desirable for very high external validity; Slide 1 • No manipulation of independent variable; • Subject groups are not the result of random assignment‚ through
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of patients‚ what is the dependent variable? In a study that examines the effect of a peer mentor on the emotional status of patients‚ what is the dependent variable? In a study that examines the effect of a peer mentor on the emotional status of patients‚ what is the dependent variable? that examines the effect of a peer mentor on the emotio In a study that examines the effect of a peer mentor on the emotional status of patients‚ what is the dependent variable?nal status of patients‚ w In a study
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Types of Variable A variable is any factor‚ trait‚ or condition that can exist in differing amounts or types. An experiment usually has three kinds of variables: independent‚ dependent‚ and controlled. Dependent and Independent Variables Independent variable The independent variable is the one that is changed by the scientist. To insure a fair test‚ a good experiment has only one independent variable. As the scientist changes the independent variable‚ he or
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this? Explanatory and Response Variables The three Principles that guide Statistics: 1. Plot the data‚ and then add numerical summaries. 2. Look for overall patterns and deviations from those patterns. 3. When there’s a regular overall pattern‚ use a simpler model to describe it. Two variables you must consider: Response Variable: Measures an outcome of a study. Example: Stroke Rate/Steel Buildings versus Brick Buildings Falling Rate Explanatory Variable: May help explain or influence changes
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kindergarten children. It focuses on their income level; how income varies with variable factors such as job type (business or service-holder‚ gender (female or male)‚ job position (rank in job sector)‚ age‚ education level (no. of years completed)‚ experience (no. of years) etc. Through a questionnaire survey‚ data are collected and applying various statistical tools and models‚ a relationship is established with income and other variables. 1.2 RATIONALE OF THE STUDY The report was prepared to fulfill
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independent‚ intervening and a moderating variable. Example of Motivation as Independent variable: “At a call centre‚ quality of solution provided to a inbound customer is dependent on the level of motivation & know how of the call centre employee responding to the call” Dependent variable - Quality of solution provided. Independent variable - Motivation & Knowledge Intervening variable Moderating variable Example of Motivation as Intervening variable: “Induction & training programs motivate
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This article considers the relationship between two variables in two ways: (1) by using regression analysis and (2) by computing the correlation coefficient. By using the regression model‚ we can evaluate the magnitude of change in one variable due to a certain change in another variable. For example‚ an economist can estimate the amount of change in food expenditure due to a certain change in the income of a household by using the regression model. A sociologist may want to estimate the increase
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problem (LPP) from set of statements. 2. To solve the LPP using graphical method ( For 2 variables) 3. To solve the LPP using primal simplex method ( For > 2 variables and all 2 variables and all mixed constraints) 5. To solve the LPP using dual simplex method ( For > 2 variables and the solution is infeasible) 6. We also have a look at the effect of changing the values of parameters on the decision variables (Sensitivity Analysis) Applications of Operations Research in functional areas of Management
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which is the number of variables‚ must be reduced for the data mining algorithms to operate efficiently. We present and discuss several dimension reduction approaches: (1) Incorporating domain knowledge to remove or combine categories‚ (2) using data summaries to detect information overlap between variables (and remove or combine redundant variables or categories)‚ (3) using data conversion techniques such as converting categorical variables into numerical variables‚ and (4) employing automated
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000‚000 Total Variable Cost = (Number of Workers * Worker’s Daily Wage) + Other Variable Costs 50‚000(workers) * $80(daily wage) = 4‚000‚000 + 400‚000(other variable cost) Total Variable Cost = 4‚400‚000 Average Variable Cost = Total Variable Cost / Units of Output per Day 4‚400‚000(total variable cost)/200‚000(units of output per day) Average Variable Cost = 22 Average Total Cost = (Total Variable Cost +Total Fixed Cost) / Units of Output per Day 4‚400‚000(total variable) + 1‚000‚000(total
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