1.0 Introduction 1.1 Background of the study Private Commercial Banks (PCBs) started their journey in Bangladesh in 1982. Since then, they play a vital role in the economic development of the country. With the help of developed banking technologies and client- focused mentality, they try to ensure quality services in quick time to their customers as per their expectation. Their prudence in selecting appropriate borrowers and sector of providing loans and monitoring them
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based on statistical analysis involves the determination of whether a true cause and effect connection between variables exists, or is it just a statistical relationship known as correlation. While there may be correlation between variables, there is not a causal relationship unless the variation in the independent variable or variables actually causes the variation in the dependent variable. Often correlation is misinterpreted as causation, as is the case in the examples presented in this essay.
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long they slept. The other group was placed in a room where jazz music played softly as they began to sleep and played throughout the night. As each group awoke, their sleep times were monitored. Dependent Variable: ______________________ Control Group: ____________________________ Independent Variable: _____________________ Experimental Group: _______________________ 2. A study was created to test the effects of fear in children. The hypothesis of the experimenters was that if babies were
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relationship between the independent variables and dependent variables. The dependent variables are influenced by the independent variables when the later is manipulated Constraints Moderating variables Moderating Variable Dependent Variable VVariabltvVariablt DDDVV
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VARIABLE Trochim (2006) defined a variable as an object, event, idea, feeling, time period, or any other type of category you are trying to measure. On the other hand, Moore and George (1993) defined a variable as any characteristic of a person or thing that can be expressed as a number whilst Frank, Little and miller (200) defined a variable as any factor that can change in an experiment. Anything that can vary can be considered a variable. For instance, age can be considered a variable because
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of case verses lecture in Business Administration. In all school environments the importance of motivating a student to actually understand the course is the intended goal of all institutes. In this synopsis we will be looking at the independent and dependent variables described throughout the study. As well as the subjects used, how they were chosen and was the study valid and reliable. The idea to perform such a study was based on proving three hypotheses by reviewing what would be the better
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for estimating the relationships among variables. It includes many techniques for modeling and analyzing several variables, when the focus is on the relationship between a dependent variable and one or more independent variables. More specifically, regression analysis helps one understand how the typical value of the dependent variable (or 'criterion variable') changes when any one of the independent variables is varied, while the other independent variables are held fixed. SIMPLE LINEAR REGRESSION
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purpose of this report is to answer the question, “what variables affect the level of crime in the United States?” With so many possible influences, the goal of this analysis will be to narrow the scope to the items which we feel will be most statistically significant when gauging the effect on the level of crime. The regression analysis methodology is best suited for this analysis since it can identify the influences of the different variables from past data and provide an equation to predict future
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Laboratory 1: Scientific Method Name: ____________________________ Group: ___________ Date:____________ 1. The Black Box Black box number: ________________________ Write your observations about the black box below: Mass:__________________________________ Describe sound: ________________________________________________________________________ Other observations:______________________________________________________________________ ______________________________________________________________________________________
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g trends, testing hypotheses, or developing models for forecasting. Regression models are able to incorporate complex mathematical functions and operands (the variables that are manipulated) to best describe the associations between sets of variables. Unlike many other statistical techniques, regression allows for the inclusion of variables that may control for confounding phenomena or risk factors. For robust analyses to be conducted, however, the assumptions of regression must be understood and
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