Week 1 Lecture Slides.pdf - OIS 2340 Business Statistics Ben Helland MBA Fall 2018 hello I am Ben Helland Contact info [email protected] 801-347-1371

Week 1 Lecture Slides.pdf - OIS 2340 Business Statistics...

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OIS 2340 Business Statistics Ben Helland, MBA Fall 2018
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hello! I am Ben Helland Contact info: [email protected] 801-347-1371 Office Hours by Appointment and 45min before each class session
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Exposures Why Everyone Should Take a Stats Class Stats as a lingual endeavor
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Statistics – Who Cares? Your first step into a larger world…
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When statistics go right From the Book - [Large firms] have made it possible for individuals to store vast amounts of data on desktop computers. But without some way to transform the data into useful information, the data these companies have gathered are of little value. Transforming data into information is where business statistics comes in.
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The Road Map Are we there yet? Definitions "Middle" Variation Probability Standardiz- ation Inference Hypothesis Testing
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Some basics Descriptive Stats - Descriptive statistics is the term given to the analysis of data that helps describe, show or summarize data in a meaningful way such that, for example, patterns might emerge from the data. Descriptive statistics do not, however, allow us to make conclusions beyond the data we have analysed or reach conclusions regarding any hypotheses we might have made. They are simply a way to describe our data. Inferential Stats - Inferential statistics use a random sample of data taken from a population to describe and make inferences about the population. Inferential statistics are valuable when it is not convenient or possible to examine each member of an entire population. From -
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Some basics Populations and Parameters - The “frame” that includes all the object, individuals or items of interest that you wish to study. Measures derived from populations are parameters Samples and Statistics - Each object, individual or item of interest that you wish to study. Drawing a number from the population represents a sample. Measures derived from samples are statistics.
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Some basics Some Sampling Techniques Non Statistical Convenience sampling: “drawn from the part of population that is close at hand” Judgment sampling Statistical Simple random sampling: “most common, each sample item has equal chance of being selected" Stratified random sampling: “subgroups (stratas) are created, each sample item within a strata has equal chance of being selected” Systematic random sampling: “every k th item is chosen, k = population/desired sample size” Cluster sampling: “population is divided into groups meant to be mini-populations, sample items are selected from cluster using any technique”
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Some basics Some Sampling Techniques Non Statistical Convenience sampling: “drawn from the part of
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