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THE U / Information System / OIS 2340 / What is the probability will be an exact number?

What is the probability will be an exact number?

What is the probability will be an exact number?

Description

School: University of Utah
Department: Information System
Course: Buisness Statistics
Professor: Professor bullough
Term: Fall 2016
Tags: Probability, distribution, Statistics, business, and ois
Cost: 50
Name: Study Guide for 2nd Midterm
Description: Hi all, This is the best study guide I could make given the limited information in class. I think the prof. will cover more material on Monday as well as the review session on Tuesday. Thanks
Uploaded: 03/02/2017
2 Pages 165 Views 3 Unlocks
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OIS 2340 MW 2:00 – 3:20  


What is the probability will be an exact number?



OIS 2340 Midterm 2 Study Guide  

Chapter 6 Continuous Probability Distribution  

1. Discrete probability distribution – the probability will be an exact number. Classic die  example.  

2. Continuous probability distribution – the probability will fall between an interval. There  is no such thing as an exact number.  

3. What you need to calculate Z-scores (both population and sample):  a. x = data value  

b. µ = population mean  

c. σ = population standard deviation  

d. x = data value ( for sample z score)

e. x(bar) = sample mean

f. s = standard deviation  

g. Population z score: σ− μ


What is the probability that will fall between an interval?



Z

=x

x xbar Z−

h. Sample z score: s

=

4. Normal Distribution  

a. Bell shaped; unimodal Don't forget about the age old question of What selection favors one extreme?

b. 50 – 50 on each side

c. Mean, median, and mode are equal  

5. Variations in normal distribution  

a. Change in mean shifts distribution left or right

b. Changing standard deviation increases/decreases the spread of the curve  6. Standard Normal Distribution  

a. Normal distribution; mean = 0; standard deviation = 1 

b. Values above mean have positive z values

c. Values below mean have negative z values


What are the variations in normal distribution?



OIS 2340 MW 2:00 – 3:20  

d. For the example, look at slide 13 in Ch6 PPT  

7. Normal Probabilities  

a. P(x) is equal to 0, when x is a continuous variable

b. Probability for a range of values, lets say x1 and x2, is the area under the curve  between x1 and x2  

c. Standard Normal Distribution Table – provides probabilities associated with z values 8. To have an easier time with calculations We also discuss several other topics like What are the large veins?

a. Know the z-score formulas  

b. Have the table ready!  

c. Have the intuition; draw the bell curve  

d. Review the ppt slides that go over the examples – not too hard!  

Chapter 7 Intro to Sampling Distributions  

1. Differentiate between Pop. Mean and Sample Mean  

a. Population Mean: µ = (∑ x)/N 

• x = values in population

• N = population size  

b. Sample Mean: xbar = (∑ x)/n Don't forget about the age old question of What is the philosophy of knowledge called?
If you want to learn more check out Where are motor proteins found?
If you want to learn more check out What is the tradition of kalinga?
We also discuss several other topics like Explain why innovation matters?

• Xbar = sample mean  

• x = Selected sample values  

• n = sample size  

2. Sample Error – difference between a statistic and a parameter  

3. Average Value of Sample Means – average value of sample means will equal the  population mean  

4. Sampling Distribution – distribution of possible values will be randomly selected from  population.  

5. Standard Deviation of Sample Means – also called standard error

a. Know the formula  

6. I don’t think most of this was covered in class. Go to the review session for thorough  preparation for the midterm; Go to Class on Monday

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