...examining models? Variables change, this helps with estimating the values of functions for the different variable values. 2. Explain the purpose of simple linear regression and scatter diagrams. Please provide a simple linear regression model and define each variable used. A scattered diagram is a statistic tool that is used to show the relationship between two variables. The scattered diagram is a combination of simple linear regression line that is used to fit the model in between two variables. The line that is drawn in the scatter chart is a model that is formed from the simple linear regression the data provides. The line equation is as follows: y=mx+b. When the calculation is done from the line, the values for “m” and “b” (the slope and intercept) are calculated with the data that is used in the simple linear regression. An example of simple linear regression is as follows: car rental for 1 day is $100 M-Thur, weekend rates will vary depending on the demand of the rentals and the number of cars. The total cost for a car rental M-Wed = constant + variable portion = $300 + $25 (number of rentals on lot) Variables: The constant portion = $300 = total for car rental for 3 days The variable portion = $25 = direct cost of car rentals available Unknown variable = supply and demand 3. Describe multiple regression analysis and discuss potential uses for this model Multiple regressions are the extension of a simple linear regression. This regression is used...
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...Part A: Motivation of this project – why did we choose this topic? The Economic Perspective of Suicide: It is interesting that we actually found this topic to be very controversial. There were some research in the 80’s and 90’s arguing that the economic loss for the whole society due to suicides (majorly due to the lost productivity) is significantly high. “There are about 30,000 individuals who completed suicide each year in the United States. According to an estimation of the costs to society of depression in 1980 calculated that the 16,111 depressed people who completed suicide in 1980 resulted in a loss of $4.2 billion due to lost productivity, which comes to a loss of $260,691 for each person who completed suicide.” However, some other researchers (Yang, B., & Lester, D) redid the cost-benefit analysis a decade later, arguing that the total savings from people who suicide, in fact, exceeds the cost to the society, and therefore there is a net savings to the society as whole. Although it does not imply that suicide should be acceptable to society, but purely in economic sense, the prevention of suicide is likely to incur economic costs to the society as does the prevention and treatment of medical illness. Why it is interesting and important: Obviously, researching on suicide is very important, no matter which of the two economic perspectives described is more reliable. If it is the case that the cost of suicide to the society is very significant that we need to do...
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...Subway is the world’s biggest sandwich chain. It overtook McDonald’s as America’s biggest fast-food restaurant by number of outlets in 2002, and achieved the same feat on a global scale in 2010. 1. Marketing Advertising Campaign * Subway targets more of the younger generation aiming at nutrition consciousness, these would include ‘empty nest 1 and 2’ (singles and newly married people) and ‘full nest 1 and full nest 2’ (family with young children and that with grownups still living with parents). * Subway also focuses on hard sell approach in terms of the functional benefits and attributes of the menu being offered while the soft sell approach is inclined towards the nutritional value gained and often gets to be criticized for the hefty amounts spent for ad campaigns and promotions. * Jared Fogle “The Subway Guy”, first came to media attention in 1999 when Men’s Health magazine did a story on how he became obese by eating junk food and not exercising and then proceeded to lose 245 pounds by eating Subway sandwiches. Fogle is now the face of Subway marketing. He tours around different schools and promotes healthy eating to children. * Mark Blackwell is Subway restaurants weight loss hero in Australia. Blackwell was inspired by Jared Fogle to develop a diet of his own design that included Subway sandwiches. * In the year 2002, the outlets’ low fat sandwiches were promoted showing Mark Blackwell having lost 42 kilograms after a year of Subway...
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...Ego Defence Mechanisms Introduction Ego psychology embodies a more optimistic and growth oriented view of human functioning and potential than do the earlier theoretical formulation. It generated changes in the study and assessment process and led to an expansion and systemization Of interceptive strategies with individuals. It fostered a re-conceptualization of the clinic worker relation ship, of change mechanisms, and of the interventive process. It helped to refocus the importance of wok of with the social environment as well as work with the family and the group. Moreover, it has important implications for the design of service delivery, large-scale social programs, and social policy. DEFINITION OF DEFENCE MECHANISM Ego-defense mechanisms are learned, usually during early childhood and are considered to be maladaptive when they become the predominant means of coping with stressors. What is EGO psychology? Ego psychology comprises a related set of theoretical concepts about human behavior that focus on the origins, development, structure, and functioning of the executive arm of the personality _the ego_ and its relationship to other aspects of the personality and to the external environment. The ego is considered to be a mental structure of the personality responsible for negotiating between the internal needs of the individual and the outside world. The following seven propositions characterize ego psychology’s view of human...
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...University of Phoenix Material Week 4 Review Worksheet Psychodynamic Theories Complete the following table. |Theorists |Main tenets of theory |Unique contributions |Limitations | |Freud | | | | | | | | | | | | | | | | | | | |Jung | | | | | | | | | | | | | | | | | | | |Adler | | |...
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...Repression occurs when a person unconsciously holds back unwanted or stressful emotions to protect themselves from reliving or acknowledging an experience. A subject can repress certain thoughts in whole or partially depending on the extent of the trauma. While attending this class I have realized that since my early teens, I have been repressing emotions that stem from sexual abuse by a person who was both a family friend and our church pastor. This realization was brought to the forefront because my wife and children enjoy attending church services and participating in church related activities, while I will make up excuses to not attend. My lack of attendance at church is a frequent subject in our household and the cause of more than a few heated discussions. The thought of going to a church service makes me uneasy and I do it only after much prodding from my wife, but even then I only go for a couple of weeks before I start making excuses again. It was after one of these discussions that I decided to use the things I had read and try to understand why I don’t like going to church. That’s when I recognized the correlation between the abuse and my lack of interest in church. Now that I recognize my apprehension toward going to church services is because I’m trying to avoid the emotions from the abuse I am going to re-evaluate my views on attending church services. Who knows, maybe I’ll like going and that will make my wife happy and relieve some stress between us. I’m not...
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...Mechanism Denial: when my grandfather passed away, I was told about it while I was still in university and after hearing it I went back to the lounge and laughed with my friends as if nothing happened. Projection: I’ve been wanting to eat healthy and stop eating junk food but I still do eat junk food and every time I see my brother having junk food I lecture him about how unhealthy and bad it, same thing happens when he asks for it. Repression: once my parents were having a fight and I just put my head phones on and started watching a movie as if nothing was happening and to this day I remember doing it but not to the extent that my sister remembers it. She says that my parents almost had a divorce but I remember it as a normal fight. Regression: when my younger brother was born. I started wanting to drink from the bottle again and sleep next to my parents. Reaction Formation: In school a lot of my classmates were super religious and had a strong opinion on praying like a person should force themselves to pray so they can be good Muslims but I don’t agree with that, I do miss prayers because I feel like a person should want to pray and it’s more than just getting the “job” done but I never said anything and would agree with them. Displacement: once before a wedding I didn’t like the way I did my hair and when my sister came to help me with my makeup I started screaming at her and telling her she’s doing things wrongly and it was because of her I didn’t want to go to the...
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...MODEL BASED TESTING Manoj Philip Mathen manoj.mathen@outlook.com Abstract: This paper is a quick glance into what is Model Based Testing, its evolution, its current state, who should use it, the techniques and tools involved and what will it mean to the enterprise in terms of the cost incurred. The paper starts with a brief exploration into some of the building blocks of MBT, followed by an attempt to define Model based Testing. This is followed by an argument on the need of Model Based Testing, and a quick overview on Model Based Testing and the approach. Next, we walkthrough 2 example scenarios, where certain models have been exhibited to showcase testing benefits. This also shows the different techniques and methods in MBT. Finally the author describes some common challenges in Model based Testing and some best practices. Introduction Model Based Testing (MBT) is very common in validating embedded systems, phones, switches etc. The model based testing was very successful and has yielded good results in these areas. This could have been the reason why practioners tried exploring the feasibility of the same in other areas of Software validation...
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...Regression Analysis Definition: Regression is used to examine the relationship between one dependent and one independent variable. After performing an analysis, the regression statistics can be used to predict the dependent variable when the independent variable is known. Regression goes beyond correlation by adding prediction capabilities. Types Of Regression Analysis: Most widely used two types of regression analysis are- I [pic] Linear Regression Analysis: When the regression is conducted by two variables or factors then is called linear regression analysis. Multiple regression analysis: Multiple regression analysis is a technique for explanation of occurrence and calculation of future actions. A coefficient of correlation among variables X also Y is a quantitative index of connection involving these two variables. In squared type, while a coefficient of purpose specifies the quantity of difference in the principle variable Y that is accounted for through the deviation in the analyst variable X. [pic][pic][pic][pic]Examples for Linear Regression Analysis: ABC a manufacturing co. where the production cost depends on their raw materials cost. Now, For the given set of x(tk in million) and y ( tk in thousand per unit) values, determine the Linear Regression and also find the slope and intercept and use this in a regression equation. |X |Y | |50 |4.2 ...
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...of pollutants that could be expected to be removed? Chapter 1.3 (word problems) 1. At sea level, the weight of the atmosphere exerts a pressure of 14.7 pounds per square inch, commonly referred to as 1 atmosphere of pressure. As an object descends in water, pressure P and depth d are linearly related. In salt water, the pressure at a depts. Of 33 ft is 2 atms, or 29.4 pounds per square inch. a. Find a linear model that relates pressure P (in pound per square inch) to depth d (in feet). b. Interpret the slope of the model. c. Find the pressure at a depth of 30 feet. d. Find the depth at which the pressure is 4 atms. 2. At low altitudes the altitude of a parachutist and time in the air are linearly related. A jump at $1,870 feet lasts 110 seconds. a. Find a linear model relating altitude a (in feet) and time in the air t (seconds). b. Find the rate of change of the parachutist in the air. c. Find the speed of the parachutist at landing. 3. The table lists average purchase prices for a house in an area. A linear regression model for average purchase price is where x represents years since 2000 and y is average purchase...
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...statistics (in this case, regression analysis) to your chosen field of study. Statistics is not a subject that you simply endure for now and then never use again. Many of the concepts covered in this course will be encountered in future courses and quite likely throughout your business career. The purpose of this project is to explore how researchers in your area of interest use the process of regression analysis. In order to do this, you will locate two articles from academic journals that pertain to your area of interest in business and contain the use of regression analysis. Your search criteria will contain one of the following majors from the UTSA College of Business: Accounting, Economics, Finance, Human Resource Management, Information Systems, Management, Management Science, and Marketing. There are several other majors, but you may find it hard to locate articles about them. In that case, it may be better to choose one of the highlighted majors above that is related to your major. Directions for finding articles: From UTSA home page Select Libraries link (bottom of page, under Current Students) Under Find Information, select Databases Select “A” under Find by Title Select ABI/INFORM – Global On first line of search terms: enter your business major from the list above (Use quotes if it is more than one word); select Subject heading (all)-SU For the two boxes on the second line enter: “linear regression” [or] “multiple regression” (be sure to include the...
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...Significance of Regression Analysis In statistics, regression analysis 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 changes when any one of the independent variables is varied, while the other independent variables are held fixed. Most commonly, regression analysis estimates the conditional expectation of the dependent variable given the independent variables — that is, the average value of the dependent variable when the independent variables are held fixed. Less commonly, the focus is on a quantile, or other location parameter of the conditional distribution of the dependent variable given the independent variables. In all cases, the estimation target is a function of the independent variables called the regression function. In regression analysis, it is also of interest to characterize the variation of the dependent variable around the regression function, which can be described by a probability distribution. Regression analysis is widely used for prediction and forecasting, where its use has substantial overlap with the field of machine learning. Regression analysis is also used to understand which among the independent variables are related to the dependent variable, and to explore the forms of these relationships. In restricted circumstances...
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...Statistical Project Assignment | Statistics for Business & Economics | | DATASET 1: SIMPLE REGRESSION ANALYSIS Variable Definition Xi = Weight of car (pounds) Yi = Price of car ($) 1. (a) Regression Model using X to predict Y Weight and Price of Car Sales | | | | | | | | | | | | | Regression Statistics | | | | | | Multiple R | 0.212585295 | | | | | | R Square | 0.045192508 | | | | | | Adjusted R Square | 0.038951936 | | | | | | Standard Error | 7883.368653 | | | | | | Observations | 155 | | | | | | | | | | | | | ANOVA | | | | | | | | df | SS | MS | F | Significance F | | Regression | 1 | 450055137.6 | 450055137.6 | 7.241725381 | 0.007915154 | | Residual | 153 | 9508567701 | 62147501.31 | | | | Total | 154 | 9958622839 | | | | | | | | | | | | | Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Intercept | 9854.041192 | 2894.819474 | 3.404026151 | 0.000847889 | 4135.063875 | 15573.01851 | Weight | 2.843766419 | 1.056751555 | 2.691045407 | 0.007915154 | 0.756058281 | 4.931474557 | Table 1 – Simple Linear Regression Model (Y and X) Simple linear regression equation Ŷi=b0+b1Xi From Table 1, we can see that b0 = 9854.0412 and b1 = 2.8438 Ŷi=9854.0412+2.8438Xi Figure 1 – Scatter Plot – Weight of Car vs Price of Car (b) Interpret the slope b1 measures the estimated change in the average value of Y as a result of...
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...Decisions Based on Demand and Forecasting Regression analysis is the description about the relationship between two variables where one is dependent and the other is independent. Regression analysis (in statistics), generally, is about any techniques that facilitate modeling and analysis of several variables. It focuses on the relationship between a dependent variable and one or more independent variables (Sykes, 2000). To be specific, regression analysis allows understanding of the typicality of value of the dependent variable changes, while any one of the independent variables is varied. At the same time, the other independent variables must be fixed. Usually, regression analysis estimates the expectation of conditions connected to the dependent variable given the independent variables (Sykes, 2000). Thus, the average value of the dependent variable is calculated using condition that the independent variables are held fixed. Not that often, regression analysis focuses on a quantile, or other location parameter of the conditional distribution of the dependent variable given the independent variables. Nevertheless, the regression function is the estimation target, which is a function of the independent variables. In regression analysis, it is also necessary to characterize the variation of the dependent variable around the regression function. This can be described by a probability distribution (Sykes, 2000). Regression analysis is usually and successfully used to...
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...occurring periodically. Answer Diff: 2 Page Ref: 682 Main Heading: Forecasting Components Key words: seasonal pattern, forecasting components 3) Random variations are movements that are not predictable and follow no pattern. Answer Diff: 2 Page Ref: 682 Main Heading: Forecasting Components Key words: random variations, forecasting components 4) The basic types of forecasting methods include time series, regression, and qualitative methods. Answer Diff: 2 Page Ref: 683 Main Heading: Forecasting Components Key words: types of forecasting methods 5) Time series is a category of statistical techniques that uses historical data to predict future behavior. Answer Diff: 1 Page Ref: 683 Main Heading: Forecasting Components Key words: time series analysis 6) Regression methods attempt to develop a mathematical relationship between the item being forecast and factors that cause it to behave the way it does. Answer Diff: 2 Page Ref: 683 Main Heading: Forecasting Components Key words: regression methods 7) Qualitative methods use management judgment, expertise, and opinion to make forecasts. Answer Diff: 2 Page Ref: 684 Main Heading: Forecasting Components Key words: qualitative methods 8) Qualitative methods are the least common type of forecasting method for the long-term strategic planning process. Answer Diff: 1 Page Ref: 684 Main Heading: Forecasting Components Key words: qualitative methods ...
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