BUS 308 What I�ve learned about Statistics Statistics for Managers

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Running Head:StatisticsPage1Cassandra Settlemyre“What I’velearnedaboutStatistics”BUS 308Statistics for ManagersInstructor: Jennifer DaleFebruary 18, 2025Discuss the key differences between descriptive and inferential statistics and theirrespective roles in data analysis. How do hypothesis testing and the selection of appropriatestatistical tests contribute to drawing accurate conclusions from research data? Provide real-world examples of when each type of statistics and test would be applicable, and explain theimportance of proper evaluation and interpretation of statistical results.Word Count Requirement: 1200-1500 words.

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What I’velearned about StatisticsPage2IntroductionThe following paper seeks to provide basic knowledge in some specific areas ofstatistical data analysis.Whilethere are no hard and fast distinctions for analyzingstatisticaldata, ensuring that you have a methodical approach is vital to an accurate analysis.The processof data analysis is thatof turning data intosignificantinformation.Data analysis is done toconvert the raw data into meaningful information. Statistics is all about this data analysis. Beforeactually working on data analysis in real world, it is important that the basic knowledge ispossessed by everybody involved in this process.Transformingdata intostatisticalinformationand then communicating itaccurately is acrucialdynamicof effective decisionmaking.Descriptive StatisticsDescriptive statistics is the tool of statistics to analyse the data. Descriptive statistics aredistinguishing from the inferential statistics, descriptive statistics aims to summarize the samplerather than use the data to learn about the population.The analysis helps in determination ofpatterns that exist in the data. Descriptive statistics simply describes the data but not present ananalysis beyond the data. One cannot make any conclusions about any hypothesis using this.Thedata, when presented tousers, is difficult to comprehend in its raw form. Sometimes the sheersize and volume of data may render it impossible to understand what it represents. Descriptivestatistics helps in proper presentation of data such that it can be understood and analyzed by theuser. For example, if we had the data about the returns from stocks of 100 companies, then thatdata would make no sense as it would be difficult to comprehend. But if that data is arranges,classified industry-wise, an average is calculated for each industry and for all the stocks, and

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