Month: April 2012

News Corporation SWOT Analysis

SWOT analysis of News Corporation which is among the largest media conglomerate operating in multiple segments which include news, entertainment, advertising, direct broadcast satellite television, publishing and other assets. News Corporation Strengths Following are the strengths of News Corporation: • Strong brand • Competitive workforce • It is amongst the top media conglomerate in terms of revenues. • It has large number of subsidiaries and most of them are profitable and well-known. • It is operating worldwide. • It is public traded company listed in NASDAQ and secondary listed in Australian security exchange. • Strong financials • It has been very consistent in expansion. • It is operating in eight segments which includes Television, entertainment, Cable TV, programming, newspapers, books publishing and etc. News Corporation Weaknesses Following are the weaknesses of News Corporation: • Involve in different scandals which negatively impact its image, • Decline in sales of publishing industry perhaps reduce the sales of News corporation • Free downloading of movies has reduced the purchasing of DVD’s. • Book publishing and magazines segment sales are low as compared to other segments of News corporation • Lack of succession planning. News Corporation Opportunities Following are the opportunities available in the industry for News Corporation: • Acquire online more news and magazine websites and blogs to increase its advertising profits. • Online streaming services over internet. • High demand for...

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MetLife Inc. SWOT Analysis

SWOT analysis is a tool which is used to evaluate the internal and external environment and make strategies for the firm. In SWOT, strengths and weaknesses are internal and controllable factors on the hand opportunities and threats are external to company. SWOT analysis of MetLife Inc. which is the leading global provider of insurance,annuities and employee benefit programs, serving 90 million customers in 60 countries. MetLife Strengths Following are the internal strengths of MetLife which can be used to exploit the opportunities and minimize the threats. High market share in the industry It has Strong financials. It is among the top names in Insurance industry. Among the best providers of insurance,annuities and employee benefits. Huge customer base (Approx: 900 million). Operations in more than 60 countries around the world. It had received award of best managed Insurance company by Forbes. MetLife is listed in fortune 500 companies within top 50 companies. Technology oriented company. MetLife Weaknesses Following are the internal weaknesses of MetLife. High operating cost. Weak grip on international market. MetLife Opportunities Opportunities available for MetLife in the Industry are: Increase Market share in existing markets Market development by offering new products. Offer new plan for corporate and individual customers. Acquisition of direct competitor. MetLife Threats Strong competition Recession or depression in US may decrease the profits margin. Increase in tax rates....

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SWOT Analysis of Lockheed Martin

SWOT analysis of Lockheed Martin which is US based company has been competing in Aerospace, defense and advance information security systems. The company was founded in 1995 by the merger of Lockheed Corporation and Martin Marietta. Its headquarter is located in Bethesda, Maryland, USA. Lockheed Corporation Strengths Following are the strengths of Lockheed corporation: Largest defense contractor around the globe. Strong cliental but major portion of revenues come form USA market specifically military. Occupies top spot in the list of US federal contractor. Strong research and development. Human resource is one of the core competencies of Lockheed Corporation It has strong product portfolio which include products  ATC systems,Ballistic missiles,Munitions,Missile defense elements,Transport aircraft,Fighter aircraft,Radar,Satellites,Atlas launch vehicles and Spacecraft. It has signed long term contracts with government agencies. Lockheed Corporation Weaknesses Following are the weaknesses of Lockheed corporation: On the top of the list in contract misconduct according to the project on government oversight database. Maximum dependency on government contract in terms of revenues and profits. Low price approach. Lockheed Corporation Opportunities Following are the opportunities available for Lockheed corporation in the industry: Acquisition and joint ventures will further strengthen its position and reduce competition. Lockheed should Increase the international market share to minimize dependency on domestic market and military revenues. Introduce more innovative defense products. New international contracts. Lockheed Corporation Threats Following are the threats for Lockheed corporation in external...

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Randomized Block Analysis

Randomize block analysis involves the analysis of variance with the factors of treatment along their interactions. Analysis of block randomized model is made through the formation of various tables. The randomized block design analysis is actually done to minimize the factors of errors appeared in the model by the observations that are done in the accounting systems. In the randomized model table drawn are separately in nature with the different distributions. The randomly errors that are detected during the analysis of the model are stated as sigma or standard deviation. The measures of the errors that are analyzed in the randomized block are based on the relationships of the treatment group and the blocking variable. The measurements in the analysis for randomized block are correlated with each other and such analysis is taken into view with the systematic repeated evaluations. The randomized block in the statistical point of view is assembled in order to reduce or minimize the effect of noise and variance in the model. The implementation of the design is evaluated in different blocks or the sub groups with the most emphasize key point is to know the variability of the each and every block less than the entire sample. The analysis for the randomized design model is generally made through the equation of regression model in order to reduce the effects of errors appeared in the...

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Post Test Only Analysis

The post test analysis model involves some of the following factors in order to be applicable on various statistical conditions. 1. Two groups 2. Work on post test measures 3. Includes two distributional measures, each of which consider mean and average 4. Evaluating treatment effect that is the difference between the groups. In the above factors the meaning o f the term difference is widely expressed which not only involve only the difference. Because it is actually affected by the variance of the group that is the difference which is evaluated by considering the low variability groups in which minimum overlapping is observed between the two groups. The consideration of difference as low variability case is important because when the variability is low the difference between the mean values is high which results in clear and absolute values and is easy to calculate. It is also stated that if the signal is high and the noise is low then the differences observed are apparent.                 Signal/ Noise = difference between the group means / dispersion of groups = mean (XT) – mean (XC)/ SE [mean (XT) – mean (XC)] = value of T In the formula, the numerator involves the actual values of the mean between the two groups that are the control group and treatment group where as the denominator involves the spread or variance of the two...

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Factorial Design Analysis

Factorial design is actually the design consisting of an experiment that examines the level effect on each factor and all the other related factors. So the factorial design analysis is the analysis made on the factorial design with the coordination of analysis of variance and the multiple regressions. The most favorable design for the treatment of statistical data is the factorial design because it creates rapid efficiency in case of the collection of the data. Firstly to examine the formation of factorial design which is comprises of two levels stated as maximum and the minimum. In the analysis of factorial design each possible factor is taken into the view. For example in case of three factor model then it is stated as two to the power three, if with four factor model  its combination are comprises of two into the ;power four which is 16 in number. Replication for all the factors is analyzed for number of times. The factorial for each case is identified separately for each and every factors level. In case of the analysis of factorial design or factorial experimental design replications are made for each factor using the analysis of variance which includes all sought of repeated evaluations. Other than the factorial design analysis the more appropriate measure is through multiple regressions. The analysis of the factorial design is computed by comparing the different effects...

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Analysis of Covariance

Analysis of covariance is actually the examination of distinctions of the mean in the dependent variable that is related with the controlled independent variables.  This is also used to compare the one variable in two or more groups in order to consider the values for the variability of variables which is known as covariates. Covariance analysis is also known to be the representative of the set of theory for the co relational data used to represent various systems of equations.  Analysis of covariance probably comprises of one way variables or two way variables with the linear regression that is the general linear model. In the analysis one variable is the dependent variable and the other used is the covariate variable. For the analysis of covariate, following inputs are required to accomplish the analysis. • Dependent variable: the continuous variable is entered with the name like VarY. • Factors:  the one variable is used for the variance category might be for one way analysis of covariance or for two way analysis of covariance like factor A or factor B. • Covariates: one or more covariate is used. • Select: it is the optional input which involves the cases of sub groups. Regarding General Linear Model Analysis of covariance involves the implementation procedure as stated for the general linear model. The following points are included in the procedure; • As in...

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What are Dummy Variables?

A dummy variable is actually a variable that is used in the statistical methods and analysis to represent the values of sub groups of the sample in numerical manner. In case of the research design the dummy variables are most probably used for creating the difference between the values that are used by the treated group. Most commonly the dummy variables are allotted with the values of 0 and 1, in which 0 is used for the control group and the 1 is used for the treatment group. These variables show significance in a way that they represent the multiple group values on the single regression equation.  Another advantage of the dummy coded variables is that they are used as nominal level variables with the appropriate distributions.  In order to understand the function of dummy variable, the regression equation is considered for the evaluation of 0 and 1 function.                                        yi = B0+B1Zi+ei From the above equation y is the value that is the concluded from the ith unit, B0 is the coefficient value for an intercept other than that B1 is the coefficient value for the slope which is actually the difference between the two groups that are treatment and control group; Zi is the fluctuating value with 0 and 1 from the treatment and control groups and the e is the residual value which comprises of the...

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The T-Test

The T Testing is done in order to examine statistically whether the means of the stated two groups are different from each other. The t test analysis is more preferable and accurate to examine the difference in the means of the two groups. For example; in case to examine T Test graphically, consider two groups one is supposed to be the control mean group and other is the treatment mean group.  The graph for both the groups is drawn in order to have the overlapped distribution,  then at this situation the T Test evaluates and explain that whether the means of  both of the groups are statistically different or not. The T Test actually examines the brief relationship between the means of two groups. For example; if there are three different presentations of the various groups with the point that there difference between the mean is actually same put they can be plotted in various ways that they does not give the same view. First situation is that in the graph the bell shaped curve is drawn with medium or moderate variability , the second situation presents the high level variability and in the second graph the two groups come up with the low level of variability but in three of the cases the two groups overlap each other.  From the various presentation of the graph, the presentation of...

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General Linear Model

General linear model is used to evaluate the statistical data in both the researches that are social as well as applied. General linear model provides the basis to the T Test, analysis of covariance, analysis of variance, regression lines and also contributed in many of the variant methods like in factor analysis, multidimensional scaling, discriminate factor analysis correlation analysis and many others.  As the model is supportive because of general creation, this model thus plays very significant role in social researches for the students.  To know about the entire knowledge and functions general linear model, some technological statistical training is required.  To attain the actual understanding of general linear model; one should first examine the case of two variables. The Two Variables Linear Model In case of the two variables a line is defined by the reference of an equation that is         Y= b0 +b1X + e In the above equation, the variable Y is the dependent variable that can be articulated in the manner as the function of the constant that is b0 and a slope b1 multiplied by the variable X.  e is denoting the possibilities of errors that occur in the evaluation.  Constant described in the equation is also being known as the intercept and the slope is referred to as the regression co efficient. For example; in case of evaluating the gross percentage average of...

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