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Statistical Reasoning - Assignment Example

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Strategic communication involves communicating of concepts, processes, or even data with an intention to satisfy an organization’s long-term strategy. Statistics is important aspect of this communication because it involves learning from data, measuring and communicating…
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Statistical Reasoning
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In strategic communication, statistics is also vital in formulation of policies and plans that require knowhow of further trends. For example, a business entity with a strategic intent of launching a new product and increasing production by 80% within the next 5 years needs statistics to achieve this. Using statistics, the business can plan concerning clients’ needs and likes. Checks on the quality of the product are more effective when using statistical methods. Decisions on new markets, site locations and profit estimation of the new products become easier with statistics.

The government also relies heavily on statistical data and methods in laying down its economic strategies and budgets. Statistical data is most accurate information available when they are estimating expected revenues and expenditures (Sridhar, 2011). Statistics therefore, is vital in strategic communication as it provides facts to support the communicated concepts, statements and processes that are intended for an organization’s strategic goal by providing grounds for advanced planning (Sridhar, 2011).

It facilitates forecasting based on current data and expected changes in the environment. A sample is taken from the population. A population is the sum of all individuals carries certain characteristics and to whom a researcher has interest in. A population can be a community of students in a college, teachers or even care racers. A sample refers to a subject of the population that is used to draw inferences regarding the entire population under study, considering some conditions. A sample constitutes different values from those of the population, and it is important for a researcher to minimize sampling error as much as possible (Hayes, 2009).

A sample is important because, it is impossible to study the entire population. This would cost

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