MBA Thesis- Entrepreneurial Business Plan Thesis

MBA - Entrepreneurial Business Plan - Thesis Example There has to be some mechanism for federal level reporting where hospitals across the country are held to it, and it’s just not a voluntary thing. We don’t have it. Voluntary reporting vastly underestimates the frequency of errors and injuries that occur† – Dr. Landriagn (Assistant Professor at Harvard Medical School) 911 Health Care Services Corporation is a privately owned firm with an aim to offer high quality healthcare services. By leveraging its services through excellent technology, firm aims to offer newest technology in patient identification and medical history storage. By employing latest technology and database tools, we aim to offer a comprehensive service which can help reduce the time and cost to record, save and retrieve patient information in hospitals and other healthcare settings. This technology will facilitate healthcare service providers at different levels and will offer a robust and a cost-saving technology which can cater to the needs at different levels including emergency departments of the hospitals. This will be a private limited company with initial share capital of $10 (m) equally divided into shares of $1 each. The initial subscribers of the business will be assuming 50% of the ownership by subscribing to propionate number of shares. Initial shareholders and subscr ibers will also serve on the management of the business and will provide their expertise and experience to run the business. This firm will be primarily a privately run business with one CEO as the head of the organization looking after day-to-day issues of the firm and devising strategies and developing strategic alliances and partnerships. A marketing team will be involved in the execution of marketing strategy through which firm can actually aim to partner with different hospitals and healthcare service providers for effecting marketing and selling of the technology. The overall idea was conceived in order to

M9 Discussion Assignment Example | Topics and Well Written Essays - 500 words

M9 Discussion - Assignment Example Everything we learned about simple linear regression is a special case of multiple regression. Multiple regression is required when a single-predictor model is inadequate to describe the true relationship between the response variable y and its potential predictors (x1, x2, x3 . . .). Adding predictors is more than a matter of â€Å"improving the fit.† A multiple regression is used to define linear relationship between a response variable y and more than one explanatory variable x. In multiple regression, more than one explanatory variable are used to explain or predict a single response variable. The multiple regression model assumes that the mean of the response variable y depends on p explanatory variables according to a linear function ‘Î ¼y = ÃŽ ²0 + ÃŽ ²1x1 + ÃŽ ²1x2 +†¦+ ÃŽ ²1xp’. In this case, the mean response is not observed, as the observed values of y vary about their means. However, we can think of subpopulations of responses, each corresponding to a particular set of values for all of the explanatory variables, and in each subpopulation, y varies normally with a mean given by the population regression equation. The regression model assumes that the standard deviation ÏÆ' of the responses is same in all subpopulations. A logistic regression is used when the response variable has only two possible values such as success or failure, live or die, acceptable or not. Logistic regressions work with odds rather than proportions. The odds are simply the ratio of the proportions for the two possible outcomes. The logistic regression model relates the log of the odds to the explanatory variable. A logistic regression models the log odds as a linear function of the explanatory variable, which is given by the equation ‘log odds = ÃŽ ²0 + ÃŽ ²1x’. A simple linear regression is a flexible way of analyzing linear relationships between two quantitative variables. A key assumption for simple linear regression model is that the deviations from the model fit