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Published byKenneth Dorsey Modified over 6 years ago
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Lesson 13.1 How do you find the probability of an event?
You will use the probability formulas. Theoretical probability is # of favorable outcomes Total # of outcomes Experimental probability is # of successes # of trials
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Lesson 13.2 How do you use the formula for permutations?
This formula is used to find the arrangement of n objects, where order is important.
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Lesson 13.3 How do you use combinations to count possibilities?
Use the formula This formula is used for the arrangement of r objects, where order doesn’t matter.
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Lesson 13.4 How do you find the probability of compound events?
You can find the probability of event A or event B occurring. You add probabilities with OR. You can find the probability of event A and event B occurring. You multiply probabilities with AND.
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Lesson 13.5 How do you identify populations and sample methods?
You can identify populations by looking for all members of a group affected by a survey. You can identify sample methods by deciding if they represent the selected population.
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Lesson 13.6 How do you compare measures of central tendency and dispersion? You can compare mean, median, and mode to find which measure best represents most of the data. You can compare measures of dispersion to find which data set covers a wider interval.
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Lesson 13.7 How do you make stem-and-leaf plots and histograms?
To make a stem-and-leaf plot Separate the data into stem and leaves. List the stems in numerical order. Write the leaves in increasing order. To make a histogram Choose equal intervals that cover all of the data values. Organize the data using a frequency table. Use the intervals from the frequency tables to draw the bars of the histogram.
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Lesson 13.8 How do you make and interpret box-and-whisker plots?
To make a box-and-whisker plot: Order the data. Find the median and the quartiles. Plot the median, the quartiles, the maximum value, and the minimum value below a number line. Draw a box from the quartiles and then connect the maximum and minimum values with “whiskers”. A box-and-whisker plot separates data into four groups: the two parts of the box and the two whiskers. Each part contains approximately the same number of data values.
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