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# STAT 130M Test 1 Review/study guide STAT 130M

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This 4 page Study Guide was uploaded by Rachel Hamilton on Monday February 8, 2016. The Study Guide belongs to STAT 130M at Old Dominion University taught by Dr. Wilson in Spring 2016. Since its upload, it has received 73 views. For similar materials see Statistics in Mathematics (M) at Old Dominion University.

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Date Created: 02/08/16

STAT 130M TEST 1 STUDY GUIDE Key terms: Statistics o Polls, studies, surveys, and other data collecting tools that collect data form a small part of a larger group so we can learn something about the larger group Population o The whole group of collection of all individuals to be studied o Goes with parameter Sample o Subset of a population o Goes with statistics Census o Collection of data from every member of a population Parameter o A numerical measurement describing some characteristics of a population Variables and Types of Data Qualitative o Categorical; consists of names and labels Quantitative o Numerical data that can be ranked o Discrete- results when the number of possible values is either finite or a countable number Example: how many people are in a line o Continuous- can take on infinite values that covers a range of values without gaps or interruptions Example: amount of milk a cow produces per day Levels of Measurement Nominal o Characterized by data that consists of names and labels. o CANNOT be ranked Ordinal o Involves data the CAN be ranked and arranged in order o Example: course letter grades Interval o Can determine difference between any two data values o There is no natural zero o Example: years, ACT scores Ratio o There is a true zero o Differences and ratios are meaningful o Zero must be the starting point o Example: prices, height, age Summarizing and Graphing Data Center o Average value that represents the middle Variation o Measure of the amount that the data values vary Distribution o Nature or shape of the spread of data over the range Outliers o Number that is vastly difference from the group of numbers o Either very low or very high Frequency distribution o Organizes and counts data Relative frequency (rf) o Percentage of values that fall into each category o Rf= (f/n)*100 Here is a raw data set for blood type within a sample. Make a frequency distribution chart and find the relative frequency A B B AB O O O B AB B B B O A O A O O O AB AB A O B A Non-categorical data Lower class limit o The smallest numbers that can actually belong to different classes Upper class limit o Largest possible value within a class Class width o Range between two lower limits o The size of the class Class boundaries o Numbers that separate classes without gaps o Average between one upper limit and the following lower class limit Cumulative frequency (cf) o The frequency of class is added to the previous and so on List steps in constructing a frequency distribution and how to check your data Histogram o A graph consisting of bars with equal width that have no gaps Measure of Center Mean o The value at the center of the data o Average Median o The middle value Mode o The value within a data set that occurs the most often Mid range o (highest-lowest value)/2 Skewed vs Symmetric Symmetric o Distribution of data where sides are roughly mirror images Skewed o Has lower and upper extremes o Right Positively skewed with tail to the right o Left Negatively skewed with tail to the left o The mean is pulled toward tail end, median is still in the middle, and mode is where the frequency is the highest Measures of Variation Range o Difference between highest and lowest value o Sensitive to extreme values Standard deviation (s) o Measure of variation of values about the mean o How far the values differ from the mean Sample variation o The square of deviation Coefficient of variation o CV= s/mean * 100 You have a data set of 5, 6, 7, 11, 15, 16, 17 find the standard deviation, sample variation, and the coefficient of variation Range Rule of Thumb The vast majority of sample values lie within two standard deviations of the mean o Min= mean- 2(s) o Max = mean+ 2(s) Empirical Rule 68% of all values fall within 1 standard deviation of the mean 95% of all values fall within 2 standard deviations of the mean 99.7% of all values fall within 3 standard deviations of the mean Label the normal distribution based on the empirical rule Z-score the number of standard deviations a value is above or below the mean finds relative position Chebyshev’s Theorem The proportion of any set of2data lying within K standard deviations of the mean is AT LEAST (1-(1/k )) K is found using the z-score

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