BMII: A Marketing Giant in the Making WEUJIGBMLLFVFC
Title: Investors Emerging Growth Stock Alert Blagman Media International: A Marketing Giant in the Making Key Points about BMII: BMII projects a total run rate of between $80-100 million in 2002. BMII currently manages an advertising and promotional campaign for MET-Rx, the nation's leader in sports supplements. Century Media, BMII's pending acquisition target, is one of the nation's largest direct marketing firms, with a dozen Fortune 1000 companies as clients. BMII has the exclusive rights to market and advertise the national video release of a four video collector's set of the best of The Red Skelton Show. Company NameBlagman Media International (OTCBB: BMII)Current Price$0.0012 (12 hundredths of one cent)52-Week High$0.5652-Week Low$0.0011Company BackgroundToday we have a look at a classic merge and conquer scenario in the $200 billion dollar Direct Response sector. The conqueror-to-be is called BMII (Blagman Media International, Inc.) The new company will combine the talents and clients of some of the biggest names in the infomercial world under the Blagman name. With its announced plans to acquire major companies such as Century Media Inc. and Wellworld Group Ltd., BMII has quickly established a gateway for major immediate revenue stream coupled with rapid internal growth. A-List clients have included the likes of Proctor Gamble, Kodak, Dainler-Chrysler, Black and Decker, Home Shopping Network, and TriStar. Total combined billings for BMII upon the completion of its acquisitions are expected to run from $80 to $100 million dollars in 2002. This will give BMII the financial leverage and the know-how to change the face of the Direct Response industry.Industry StatsAccording to the Direct Marketing Association (DMA), U.S. direct marketing expenditures , currently at $191.6 billion, are expected to continue to grow annually at 7.1% from 2002 until 2005. Moreover, U.S. sales revenue due to direct marketing is estimated to reach more than $1.8 trillion for 2001. Through 2005, such sales are estimated to grow by 9.6% annually to reach $2.7 trillion. Again- Direct Response will cause $2.7 trillion (estimated) in sales by 2005. This figure goes to show the effectiveness of direct marketing as well as the likelihood that demand for Direct Response will continue to grow over the years.BMII's Growth StrategyRecognizing the opportunity for strategic consolidation in the Direct Response industry, the management of Century Media and Blagman decided to utilize BMII to facilitate the acquisition strategy. Through its public position, BMII assumed the lead role in the financing and negotiated the acquisition for a combination of stock and cash The company's senior management and board will consist of a combination of senior managers from both companies. Currently, no other direct independent competitor to BMII is in the field of Direct Response having the breadth and depth of its combined enterprises. At present, 99% of the pure play infomercial business is privately held. And for good reason. The margins offered by Direct Response sales are three and four times greater than traditional bricks-and-mortar retail. Profit potential that makes BMII a stock with tremendous upside. BMII CEO Robert Blagman understands the Infomercial sector. Says Blagman, The primary purpose of these reverse mergers was to make BMII public and create a new BMII, a vehicle with which to build a media-buying infrastructure. BMII will streamline operations, combine miscellaneous expenses, and create synergies within this larger structure to increase economies of scale and lower costs-per-eyeball for their clients.In ConclusionGiven its accomplishments and current plans, BMII appears to have great upside potential in the exciting infomercial market. Blagman Media International has demonstrated is ability to capture substantial clients, as evidenced by its impressive client base. The acquisitions of Century Media and Wellworld will provide BMII with an even larger client base with plenty of experience under its wing. With an expected $80-100 million in billings for 2002 and the prospect of additional mergers, acquisitions, and new ventures, BMII gives investors plenty to look at given its price of just fractions of a penny per share. To be removed from future mailings, please respond to this email with Remove in the subject line. DISCLAIMER: Information within this email contains forward looking statements within the meaning of Section 27A of the Securities Act of 1933 and Section 21B of the Securities Exchange Act of 1934. Any statements that express or involve discussions with respect to predictions, expectations, beliefs, plans, projections, objectives, goals, assumptions or future events or performance are not statements of historical fact and may be forward looking statements. Forward looking statements are based on expectations, estimates and projections at the time the statements are made that involve a number ofrisks and
meta analysis with multilevel data
Hello, i have got a problem concerning computing effect sizes in meta analysis: Does anybody know meta analytic studies using data originating primary from multilevel data? If they dont report the simple correlation matrix, does anybody know how to compute the ES(r) from the coefficients reported in studies using multilevel analysis? Greetings, Stefan = Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at http://jse.stat.ncsu.edu/ =
CATPCA
Hi! Does anybody know of a reference for what CATPCA in SPSS (v10) does and how it does it? I contacted SPSS but they don't even bother to answer. Thanks Joao = Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at http://jse.stat.ncsu.edu/ =
Low cost quality conference calls
Title: Take Control Of Your Conference Calls Crystal Clear Conference CallsOnly 18 Cents Per Minute! (Anytime/Anywhere) No setup fees No contracts or monthly fees Call anytime, from anywhere, to anywhere Connects up to 100 Participants International Dial In 18 cents per minute Simplicity in set up and administration Operator Help available 24/7 Get the best quality, the easiest to use, and lowest rate in the industry. If you like saving money, fill out the form below and one of our consultants will contact you. Required Input Field* Name* Web Address Company Name* State* Business Phone* Home Phone Email Address* Type of Business c 1999-2002 CCFL To be removed from our distribution lists, please Click here.. * Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at http://jse.stat.ncsu.edu/
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Re: Interpreting mutliple regression Beta is only way?
Rich Ulrich [EMAIL PROTECTED] wrote in message Thanks Rich, most informative, I am trying to determine a method of comparing apples to oranges - it seems an improtant thing to try to do, perhaps it is impossible . I am trying to determine which is better, glycemic index or carbohydrate total in predicting glycemic load (Glycemic load=glycemic index*carbohydrate). my results as a matrix: GI load GI Carb GI load 1.000 GI .5331.000 Carb .858.1241.000 So it seems that carb affects GI load more than does GI.. but this is on ALL foods.. (nobody eats ALL foods so cannot extrapolate to human diet) but I don't think you're allowed to do this kind of comparison as Carb and GI aretotal different values: I suspected that you would be allowed to make the comparisons if you use Betas, ie. measure how many standard deviation changes of GI and Carb it requires.. If it takes a bigger standard deviation of Carb then you could say that it is more likely that carb has a bigger effect on glycemic load. you seem to suggest that even using standard deviation changes, you cannot compare apples to oranges. Which sounds right but is dissapointing.. = Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at http://jse.stat.ncsu.edu/ =
Re: CATPCA
Go to WWW.SPSS.COM key CATPCA into the edit box click search João Maroco wrote: Hi! Does anybody know of a reference for what CATPCA in SPSS (v10) does and how it does it? I contacted SPSS but they don't even bother to answer. Thanks Joao = Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at http://jse.stat.ncsu.edu/ =
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Re: Interpreting mutliple regression Beta is only way?
Wuzzy [EMAIL PROTECTED] wrote in message [EMAIL PROTECTED]">news:[EMAIL PROTECTED]... Rich Ulrich [EMAIL PROTECTED] wrote in message Thanks Rich, most informative, I am trying to determine a method of comparing apples to oranges - it seems an improtant thing to try to do, perhaps it is impossible . I am trying to determine which is better, glycemic index or carbohydrate total in predicting glycemic load (Glycemic load=glycemic index*carbohydrate). my results as a matrix: GI load GI Carb GI load 1.000 GI .5331.000 Carb .858.1241.000 So it seems that carb affects GI load more than does GI.. but this is on ALL foods.. (nobody eats ALL foods so cannot extrapolate to human diet) but I don't think you're allowed to do this kind of comparison as Carb and GI aretotal different values: I suspected that you would be allowed to make the comparisons if you use Betas, ie. measure how many standard deviationGlycemic load=glycemic index*carbohydrate changes of GI and Carb it requires.. If it takes a bigger standard deviation of Carb then you could say that it is more likely that carb has a bigger effect on glycemic load. you seem to suggest that even using standard deviation changes, you cannot compare apples to oranges. Which sounds right but is dissapointing.. The glycaemic index is calculated as the area under the blood glucose curve for the two hours (or 3 hours for diabetics) after ingesting enough of a food to include 50 grams of carbohydrate, divided by the same area after ingesting 50 grams of pure glucose, expressed as a percentage. In some cases a reference food other than glucose is used. If the area under the curve is the glycaemic load you are studying I would expect the model Glycemic load=glycemic index*carbohydrate to fit the data very well when the carbohydrate content is near 50 gm, providing all the glycaemic indices have been calculated on the same basis. Using correlations or beta coefficients as you are doing is appropriate when linear relationships are involved, but not to test for goodness of fit to this model. What would be of interest would be a plot of the difference between the predicted glycaemic load and the observed value,against carbohydrate, especially for carbohydrate values far from 50 gm. If I have a meal of mainly of eggs or meat, the total carbohydrate content is very low, so the glycaemic load calculated from the formula may be wrong. One difficulty with the whole Glycaemic Index approach is that there is not, as far as I know, any way of calculating the glycaemic load from foods like cheese,eggs and meat. If the body needs glucose, it will be made from fat and protein foods. It is not surprising that it could be hard to persuade volunteers to ingest 8500 grams of processed cheese, containing 50gm of carbohydrate, in order to determine its glycaemic index :-) I would like to see another index constructed giving the glycaemic load produced by 100 gm of each food, rather than the load produced by that amount of food which contains 50gm of carbohydrate. = Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at http://jse.stat.ncsu.edu/ =
Re: Interpreting mutliple regression Beta is only way?
Wuzzy [EMAIL PROTECTED] wrote in message [EMAIL PROTECTED]">news:[EMAIL PROTECTED]... Rich Ulrich [EMAIL PROTECTED] wrote in message Thanks Rich, most informative, I am trying to determine a method of comparing apples to oranges - it seems an improtant thing to try to do, perhaps it is impossible . I am trying to determine which is better, glycemic index or carbohydrate total in predicting glycemic load (Glycemic load=glycemic index*carbohydrate). my results as a matrix: GI load GI Carb GI load 1.000 GI .5331.000 Carb .858.1241.000 So it seems that carb affects GI load more than does GI.. but this is on ALL foods.. (nobody eats ALL foods so cannot extrapolate to human diet) but I don't think you're allowed to do this kind of comparison as Carb and GI aretotal different values: I suspected that you would be allowed to make the comparisons if you use Betas, ie. measure how many standard deviationGlycemic load=glycemic index*carbohydrate changes of GI and Carb it requires.. If it takes a bigger standard deviation of Carb then you could say that it is more likely that carb has a bigger effect on glycemic load. you seem to suggest that even using standard deviation changes, you cannot compare apples to oranges. Which sounds right but is dissapointing.. The glycaemic index is calculated as the area under the blood glucose curve for the two hours (or 3 hours for diabetics) after ingesting enough of a food to include 50 grams of carbohydrate, divided by the same area after ingesting 50 grams of pure glucose, expressed as a percentage. In some cases a reference food other than glucose is used. If the area under the curve is the glycaemic load you are studying I would expect the model Glycemic load=glycemic index*carbohydrate to fit the data very well when the carbohydrate content is near 50 gm, providing all the glycaemic indices have been calculated on the same basis. Using correlations or beta coefficients as you are doing is appropriate when linear relationships are involved, but not to test for goodness of fit to this model. What would be of interest would be a plot of the difference between the predicted glycaemic load and the observed value,against carbohydrate, especially for carbohydrate values far from 50 gm. If I have a meal of mainly of eggs or meat, the total carbohydrate content is very low, so the glycaemic load calculated from the formula may be wrong. One difficulty with the whole Glycaemic Index approach is that there is not, as far as I know, any way of calculating the glycaemic load from foods like cheese,eggs and meat. If the body needs glucose, it will be made from fat and protein foods. It is not surprising that it could be hard to persuade volunteers to ingest 8500 grams of processed cheese, containing 50gm of carbohydrate, in order to determine its glycaemic index :-) I would like to see another index constructed giving the glycaemic load produced by 100 gm of each food, rather than the load produced by that amount of food which contains 50gm of carbohydrate. = Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at http://jse.stat.ncsu.edu/ =
Re: Interpreting mutliple regression Beta is only way?
Wuzzy [EMAIL PROTECTED] wrote in message [EMAIL PROTECTED]">news:[EMAIL PROTECTED]... Rich Ulrich [EMAIL PROTECTED] wrote in message Thanks Rich, most informative, I am trying to determine a method of comparing apples to oranges - it seems an improtant thing to try to do, perhaps it is impossible . I am trying to determine which is better, glycemic index or carbohydrate total in predicting glycemic load (Glycemic load=glycemic index*carbohydrate). my results as a matrix: GI load GI Carb GI load 1.000 GI .5331.000 Carb .858.1241.000 So it seems that carb affects GI load more than does GI.. but this is on ALL foods.. (nobody eats ALL foods so cannot extrapolate to human diet) but I don't think you're allowed to do this kind of comparison as Carb and GI aretotal different values: I suspected that you would be allowed to make the comparisons if you use Betas, ie. measure how many standard deviationGlycemic load=glycemic index*carbohydrate changes of GI and Carb it requires.. If it takes a bigger standard deviation of Carb then you could say that it is more likely that carb has a bigger effect on glycemic load. you seem to suggest that even using standard deviation changes, you cannot compare apples to oranges. Which sounds right but is dissapointing.. The glycaemic index is calculated as the area under the blood glucose curve for the two hours (or 3 hours for diabetics) after ingesting enough of a food to include 50 grams of carbohydrate, divided by the same area after ingesting 50 grams of pure glucose, expressed as a percentage. In some cases a reference food other than glucose is used. If the area under the curve is the glycaemic load you are studying I would expect the model Glycemic load=glycemic index*carbohydrate to fit the data very well when the carbohydrate content is near 50 gm, providing all the glycaemic indices have been calculated on the same basis. Using correlations or beta coefficients as you are doing is appropriate when linear relationships are involved, but not to test for goodness of fit to this model. What would be of interest would be a plot of the difference between the predicted glycaemic load and the observed value,against carbohydrate, especially for carbohydrate values far from 50 gm. If I have a meal of mainly of eggs or meat, the total carbohydrate content is very low, so the glycaemic load calculated from the formula may be wrong. One difficulty with the whole Glycaemic Index approach is that there is not, as far as I know, any way of calculating the glycaemic load from foods like cheese,eggs and meat. If the body needs glucose, it will be made from fat and protein foods. It is not surprising that it could be hard to persuade volunteers to ingest 8500 grams of processed cheese, containing 50gm of carbohydrate, in order to determine its glycaemic index :-) I would like to see another index constructed giving the glycaemic load produced by 100 gm of each food, rather than the load produced by that amount of food which contains 50gm of carbohydrate. = Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at http://jse.stat.ncsu.edu/ =
cell-counts question
Dear Friends, Here is an exam question which I don't know how to do. Can anyone help me? The question is a biostatistician was asked to analyze some data regarding cell counts, and the values were reported like 6.27x10^7, 72.5x10^7, 3.42x10^7, etc. rather than using the data exactly as reported, the biostatistician used the values as 6.27, 72.5, 3.42, etc. what effect does this have on estimation of mean and standard deviation? What effect does this have on hypothesis testing about the mean? Why? Thank you very much for your help. Christine, = Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at http://jse.stat.ncsu.edu/ =
