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Statistic 154 Notes 8/22 and 8/23

by: Amanda Selly

Statistic 154 Notes 8/22 and 8/23 STATS 154

Marketplace > Minnesota State University - Mankato > Statistics > STATS 154 > Statistic 154 Notes 8 22 and 8 23
Amanda Selly
Minnesota State University, Mankato
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These are the in class notes from Monday and Tuesday of this week!
Elementary Statistics
Kyle Zachrich
Class Notes
Statistics, Math




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This 4 page Class Notes was uploaded by Amanda Selly on Wednesday August 24, 2016. The Class Notes belongs to STATS 154 at Minnesota State University - Mankato taught by Kyle Zachrich in Winter 2016. Since its upload, it has received 39 views. For similar materials see Elementary Statistics in Statistics at Minnesota State University - Mankato.

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Date Created: 08/24/16
Elementary Statistics Notes Amanda Selly August 22, 2016 Statistics: is the practice of taking data and making inferences with that data   Inferential Statistics:    Ex. In general students Descriptive Statistics: who are in STAT 154 are   taking 14.3 credit hours  Ex: the average number of credits in STAT 154-02  Unsafe and difficult to is 14.3 rely on   V.S  Tries to predict the  Is safe and clearly shown future    Uses what we currently  No outside knowledge needed know to predict what we  May use mean median don’t know, which is unreliable because there and mode  It is the data that we is no way of knowing what will happen currently have and is proven based on the data   Data or Datum: a piece of information that is collected from a subject Note: a subject doesn’t have to be a person; it is simply whatever we are collecting data from at that time   Quantitative:    Expressed in words or Quantitative: categories    We sometimes use  Expressed in numbers numbers as a "code" for    A calculated quantity V.S particular categories however that doesn’t or amount   change that it's a category     Continuous:    Infinite number of possible values   Discrete:  I.e. Height  Finite number of   V.S possible values  I.e. Age: you can only   be one age at any  It doesn’t matter particular time. Even if you count seconds there what value you define there is always going to will always be a set number be more in between   Elementary Statistics Notes Amanda Selly August 23, 2016 Nominal: no set order of categories  i.e. Which color of car is better? Even though you might have personal opinions and ideas there is no logical order of where each color goes. Each category is equal and cannot be ranked Ordinal: There is a logical order  i.e. A survey is taken to see who like mom and pops ice cream shop. Subjects had to respond with good, bad, great and super great. There is obviously an order that these rankings can be put in and some are better or worse than others. Interval: The numerical difference between the data points is known.  i.e. so on Monday the temperature outside is 1 degree and on Tuesday the temperature is 32 degrees. We know that the difference or interval between degrees is 31 degrees,  i.e. I know that Jim's gpa is a 3.6 and Barbra's gpa is 2.5. the interval between their gpas is 1.1 Ratio: We can compare the two points as a ratio when we have 0 as a reference point  A set of data cannot be a ratio if it can go below zero like temperature. i.e. So going back to Monday and Tuesday, you would not be able to set up a ratio 1:32 because you cannot say that it was 32 times hotter on Tuesday than it was on Monday. It doesn't make sense because the Fahrenheit temperature scale goes below zero.  i.e. Swimming times always start at zero because obviously you cannot swim in less then zero seconds even though most swimmers want to. Anyways if you swim 25 meters in 10 seconds and I swim in 20 seconds there would be a clear 1:2 ratio or you could say that you swam twice and fast as me or I swam half as fast as you. This is a ratio because the reference point is set at 0. Studies:  What are the qualities of a good or a bad study?   Good    The study is blind and random Bad    You have more than 30 subjects  Biased  There are only 3 people  Each category is even  Uneven population or sample sizes    Ideally to have a really good study you would poll the entire population of people you are interested in. So if you're interested in what the average age in the USA you would literally have to go door to door and ask every single person how old they are. Now that’s just never going to happen, we don’t have the time or the resources to talk to every single person in the country, not to mention that new people are being born literally every second. This is why we have Samples which are just a small group inside the population. The results are called different things based on if you're testing a sample or a population: Population: Parameter Sample: Statistic i.e. Is this a parameter or statistic?  The average income per month for freshman at Mankato is 40$ It’s a statistic because we're just looking at freshman at Mankato  68% of all the streets in Minnesota have pot holes This is a parameter because they tested the entire population of potholes. Brief History:  Statistics was started in the 1970s  It is new, modern and always changing  Started in order to evaluate the data found in the census  Probability is the basis of statistics


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