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QMET 352

by: Alexandra Casey
Alexandra Casey
University of Louisiana at Lafayette
GPA 3.9
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About this Document

Here are the notes for the first two classes. It covers the basic concepts for the 1st exam.
Advanced Business Statistics
Dr. John Tanner
Class Notes
Statistics, business, Dr. Tanner, UL




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This 3 page Class Notes was uploaded by Alexandra Casey on Friday January 29, 2016. The Class Notes belongs to QMET 352 at University of Louisiana at Lafayette taught by Dr. John Tanner in Spring 2016. Since its upload, it has received 228 views. For similar materials see Advanced Business Statistics in Business at University of Louisiana at Lafayette.

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Date Created: 01/29/16
Key Box: ***: Know for test QMET 352: Advanced Business Statistics besides definitions NOTE FROM DR.TANNER: ***: Definition ***: Titles PLEASE ONLY USE THESE NOTES AS A REFERENCE. DO NOT MISS CLASS JUST BECAUSE YOU CAN BUY THE NOTES. 1/14  T-test: a method for determining if there is a statistically significant difference between 2 means. o 2 means could be:  2 sample means  1 sample mean, 1 population mean  Big Four The four main questions asked during working problems and test problems: 1. What is a Null Hypothesis?  Null Hypothesis (H0): one sentence that states that the 2 means in the problem are EQUAL. Nothing more than an educated guess.  This is how you start a problem- it is simple, short, and very specific. *** First 6 words of ANY hypothesis: “There is no significant difference between…”  What comes after  a specific description of the 2 means (must differentiate between the sample or population mean) 2. How many tails does this problem have? 1-tail test check to see if the problem is one sided. In other words look for key words after the started means (less than, more than, higher, lower, etc.) 2-tail test check to see if the problem is determining a difference, 2 sided. Key words to look for: specified, exact, etc. 2 sided is looking for on both sides of the means and figuring out if the means are EXACTLY the same or not. 3. What is the level of significance? Level of significance(Risk Factor/ L of S/ α- alpha symbol): the percent chance we are willing to take that our conclusions might be wrong i. Most popular levels of significance  0.01, 0.2, 0.5, 0.10 ii. ALWAYS IF LEVEL IS NOT GIVEN USE 0.05! iii. Table value? t-critical= table t & table z  Use t-critical for both 1-tail test and 2-tail test 1. ANY 2-tail test must put +/- (±) sign in answer 2. 1-tail test put EITHER + or - 4. What is the ACR? i. Action- Accept or Reject Null Hypothesis ii. Conclusion - What is the problem looking to solve, were they right? Explain. iii.Recommendations - based off of conclusion, must match the conclusion NEVER USE THE WORDS “significant” or “difference” IN ACR As long as your recommendation makes sense, you are fine.  P-value- the value that determines whether or not to reject or accept the null hypothesis o P (T<=t) HOW TO GET EXCEL TO CREATE A TABLE: Click data tab  Data Analysis- drop down box  File -options - ADD- INS  Analysis Tool Pak -GO…  Data Analysis ---- OK Rest of class- practice problems. 1/19 More practice problems.  Null Hypothesis- think about how you write it. Can someone outside this class understand it o It will go away for a few exams, but WILL be on the final.  Table- value= t-critical(same thing!) o T- critical is easy to find if you get the tails correct, so don’t screw that up o Question on exam: “What is t-critical?”  We will be given the table, just have to decipher the table and explain it. ***ONLY 1-tail test: One set of sample data  if the sample mean is greater than the population mean, t- DOES NOT critical is positive. APPLY TO 2-TAIL  If the sample mean is less than the population mean, t-critical TESTS is negative  P-value o NEVER WILL CHANGE- ALWAYS TRUE: If the p-value in a problem is given, if it is less than the level of significance, REJECT the null hypothesis  REJECT = rejection of the means being equal If the p-value in the problem is LESS than the level of significance, REJECT the null hypothesis  ACCEPT = the means are equal If the p-value in the problem is GREATER than the level of significance, ACCEPT the null hypothesis ***Only look at the numbers visually/ logically when you are rejecting the null hypothesis. DO NOT compare the numbers visually if you are accepting because statistically the numbers are the same if you are accepting the null hypothesis.


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