Statistics for Decision- Making in Business - Maricopa Community ...

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d. Is the firm‟s goal to conduct descriptive or inferential statistics 3. In a quality control process, 250 packages of cheese are randomly selected from an assembly line. Each package of cheese will be described as either “pass” or “fail,” depending on whether or not it passes the inspection. a. Describe the sample. b. Describe the population. c. Quality control will fail if more than 1% of the packages fail. How many packages must pass 4. Two datasets have a range of 30. Describe how it is possible that one dataset is considered to be more spread out that the other dataset. 5. One hundred randomly selected CGCC students are surveyed and asked, “Do you believe that racism is an issue in the college setting” The survey makers would like to generalize to college students. What is wrong with their study Statistics for Decision-Making in Business © Milos Podmanik Page 20
1.3Statistics in Excel When conducting an analysis of realistic amounts of data, it is tiresome, mundane, and even unfeasible to carry out computations by hand. Microsoft Excel is by far a more powerful and accessible piece of software that does this all for us. As such, we seek to better understand how it works in this section. All images below come from the most recent version of Microsoft Excel. Excel is a spreadsheet-based software. This means that each entry, or cell, represents one piece of information that is all a part of a larger grid of cells. A cell may contain numerical or textual information. 1.3.1 Sum(), Average(), Min(), and Max() Eventually, you will learn to make beautiful spreadsheets, but we are now only concerned with some basic features. Let‟s begin by entering the following accounting data from Section 1.2: Statistics for Decision-Making in Business © Milos Podmanik Page 21
Page 1 and 2: Statistics for Decision- Making in
Page 3 and 4: A Note to Students This book is far
Page 5 and 6: 6.3 Confidence Interval for ̂ 202
Page 7 and 8: which has undergone no additional r
Page 9 and 10: of transporting such an animal. Not
Page 11 and 12: Although far from last, we will con
Page 13 and 14: Account Type Revenue ($) New $5,296
Page 15 and 16: For the present time, we‟ll proce
Page 17 and 18: Row Labels Average of Revenue ($) M
Page 19: (SOURCE: Essentials of Modern Busin
Page 23 and 24: We can make it a bit more presentab
Page 25 and 26: For measures such as the range, Exc
Page 27 and 28: We get: We can do the same for Old.
Page 29 and 30: Chapter 2 Visual Representations of
Page 31 and 32: We now have to enter a formula for
Page 33 and 34: We know from the data that this val
Page 35 and 36: Alternatively, it is possible to in
Page 37 and 38: 16 14 12 10 8 6 Series1 4 2 0 SD D
Page 39 and 40: Selected the copied graph. In Chart
Page 41 and 42: 2. The following data represents pe
Page 43 and 44: Frequency 2.2 Visualizing Quantitat
Page 45 and 46: You can either choose to have Excel
Page 47 and 48: If we had additional variables, the
Page 49 and 50: Select PivotChart and select the fi
Page 51 and 52: Frequency To make solid black lines
Page 53 and 54: Relative Frequency Histogram of Cal
Page 55 and 56: a. Using Excel, find the mean and r
Page 57 and 58: ̅ ̅ account for this discrepancy,
Page 59 and 60: 2.3.2 Percentile Another useful too
Page 61 and 62: 2.3.4 Rank What if, on the other ha
Page 63 and 64: Check the “Analysis ToolPak” an
Page 65 and 66: You‟ll immediately notice that a
Page 67 and 68: ̅ 2.4 Descriptive Statistics - Var
Page 69 and 70: √ ∑( ̅) √ √ This is what w
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This gives us a nice measure of how
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We can immediately see the mean and
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Lastly, a normal curve is the most
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Frequency ̅ Histogram of TV's Owne
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58.3 34.6 35.5 45.4 38.6 63.8 53.9
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Chapter 3 Probability and Decision
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Proportion of Rainy Days 1.2 Propor
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This means that if samples of HFCS
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Are we confident in accusing a lung
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3.2 Joint Probability In the previo
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Company 1 Choices Y Y Y Y Y Y Y Y N
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There is less than a 1% chance that
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We can now see that the situation i
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sequence, one ball is chose at rand
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3.3 Probability of Unions Imagine t
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Physical .20 .10 .30 Mental .40 .30
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SOLUTION: We first arrange this inf
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Homework Problems - 3.3 1. A gaming
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3.4 Conditional Probability In many
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) : The Arizona Cardinals make it t
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We could just as well have written,
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That is, the probability that the c
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This can happen in one of two ways:
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f. All numerical red cards are remo
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3.5 Combinations and Permutations R
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1 st Bushel 2 nd Bushel U1 U1 U2 U2
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Which, in its final state gives: Th
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Combination - Order Does NOT Matter
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( ) There is only a .9% chance that
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1. Are repeats/replacements allowed
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Object 4 Object 5 Also notice that
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e. 2. Your classmate was absent whe
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3.6 Expected Value Imagine that you
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An expected value is actually not s
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Where The expected value is: , - (
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SOLUTION: We first note that there
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Probability 0.7 0.6 0.5 0.4 0.3 0.2
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Statistics for Decision-Making in B
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For men, we see that the most frequ
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So, we had 10 trials and wanted to
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Example 1: A fair-two sided coin is
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( ) ( ) ( ) ( ) Example 2: A fair,
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Expected Value of a Binomial Random
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f. What is the probability that g.
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Probability For instance, we see th
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Density 0.25 Time Speng Waiting in
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Suppose we wish to find ( ), that i
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Density Resulting in a standard dev
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Density Without going into detail h
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a. What is the probability that the
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Statistics for Decision-Making in B
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As you can see, this is a difficult
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We wish to know the area of the sha
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We can easily find that the probabi
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In the second section, we can check
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Chapter 6 Sampling Distributions an
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Thus, the standard deviation would
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1.7 to 1.8 1.8 to 1.9 1.9 to 2 2 to
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2.4 to 2.5 2.5 to 2.6 2.6 to 2.7 2.
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The Central Limit Theorem (CLT) has
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can set this up in our applet by ha
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3) We cannot use this sample to cal
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Thus, we need to find the lower and
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We see that the standard deviation
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√ The lower limit is: √ And the
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following data was collected on the
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{ So, we have a set of twenty 1‟s
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DULY CAUTIONED: The assumptions her
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Homework Problems -6.2 1. In a samp
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Since this is a mathematical questi
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Example 3: Many older homes have el
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Hypothesis Test Conclusion Test Say
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Hypothesis Test Conclusion Since yo
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SOLUTION: d. A generic conclusion s
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9. Based on the “Structure of a H
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1.2 Descriptive VS. Inferential Sta
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Relative Frequency 35% 30% 25% 20%
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Symmetric: 35 30 25 20 15 10 5 0 10
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Repair Cost Mean 971 Standard Error
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el freq Nitrous Oxide (thous. Tons)
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Probability Pizza Size Distribution
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e. ( ) f. ; the average response ti
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2. a. The long-run proportion of al
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e. 20% of all children are expected
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e. The middle 50% score between abo
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5. b. This might indicate that the
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̅ We have that ̅ and √ . So our
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6. This is the probability that we
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