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Download Ch. 1.1,1.2,1.3 - STATS STATS STATS STATS STATS!
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Ch. 1.1,1.2,1.3 GETTING DOWN TO BASICS 1.1 Part One Questions to Start Off 1. What is the difference between Quantitative and Qualitative Graphs 2. What are Some Important Qualitative and quantitative graphs 3. What is the Difference Between a Histogram and a Bar Graph 4. Why are Stem and Leaf plots not good for large sets of data 5. (Personal Question) What would you like to focus upon in this Ch. 1.1 Part 2- OGIVES Are used to show proportion Compose of three factors; Relative Frequency, Cumulative Frequency ,and Relative Cumulative Frequency Relative Frequency is How Many data points are in your given range, divided by # of data points Cumulative Frequency is all the relative frequencies of a given range and all the other given ranges before it added up Relative Cumulative Frequency is all the relative frequencies of a given range and all the other given ranges before it added up, then divided by # of data points Ch. 1.2- Start Off Questions What is the Difference between mean, median, and mode What does it mean to be “Resistant” What are the 3 s’ What is the difference between mean and standard deviation compared to median and IQR What measures of spread are resistant and what are not (Personal) is their any questions that you have? 1.2- Boxplots Boxplots use median and percentiles 1st percentile, 25th, median, 75th, 100th See board for explanation 1.2- Linear Transformations When changing all the data linearly, use the equation y= a+bx What does this equation tell us about how we are changing shape and spread Adding “a” will only change the spread Multiplying by b will change the shape and the spread P.3 Probability( A little of it) What is Probability Only works in the long run Will Be Reviewed in Later Chapters Ch. 2- Questions What is a z-score How do you get a z-score What does a histogram represent What is standard deviation What is the area under a density curve What are the different types of density curves What is a very special type of density curve and what is so special about it Any More general questions Ch. 2- Normal Curves 68, 95, 99.7 rule Can be used to represent countless situations in real life For example, the mean height of trees or Acidity of Rain Be careful when using the Normal Distribution, because 1. Doesn’t represent everything 2. Don’t abuse the normal curve and what it tells you, it can fit a lot of data but it isn’t the be all end all of it 3. Must Prove that it is a normal distribution(How, you will see in the next slide) Ch.2 Normal Probability Plot A Normal Probability plot shows whether the Data is Normal or Not What is the Idea behind it(Direct to board) If the plot shows a somewhat straight line, it is normal Beware the curved and weird data Don’t stress over small deviations Can also use a histogram to show normality, but NPP is better
