VCU STAT 210  232247731StatisticCheatSheet (2 pages)
Previewing page 1 of 2 page document View the full content.232247731StatisticCheatSheet
Previewing page 1 of actual document.
View the full content.View Full Document
232247731StatisticCheatSheet
0 0 46 views
 Pages:
 2
 School:
 Virginia Commonwealth University
 Course:
 Stat 210  Basic Practice of Statistics
Basic Practice of Statistics Documents

4 pages

57 pages

84 pages

26 pages

63 pages

73 pages

78 pages

86 pages

54 pages

30 pages

76 pages

71 pages

78 pages

54 pages

59 pages

40 pages

80 pages

56 pages

68 pages

46 pages

45 pages

44 pages

78 pages

4 pages

4 pages

3 pages

4 pages

4 pages

3 pages

4 pages

3 pages

4 pages

3 pages

67 pages

2 pages

44 pages

32 pages

64 pages

3 pages

4 pages

75 pages

96 pages

74 pages

68 pages

73 pages

77 pages

55 pages

58 pages

79 pages

68 pages

99 pages

111 pages

122 pages

55 pages

55 pages

56 pages

95 pages

98 pages

85 pages

73 pages

53 pages

55 pages

74 pages

63 pages

72 pages

50 pages

48 pages

45 pages

57 pages

43 pages

34 pages

64 pages

37 pages
Sign up for free to view:
 This document and 3 million+ documents and flashcards
 High quality study guides, lecture notes, practice exams
 Course Packets handpicked by editors offering a comprehensive review of your courses
 Better Grades Guaranteed
Unformatted text preview:
Sample proportion The mean value of is denoted by and the standard deviation of is denoted by Rule 1 This means that the values from many different random samples will tend to cluster around the actual value of the population proportion Rule 2 Rule 3 when n is large and is not too near 0 or 1 the sampling distribution is approximately normal The Central Limit Theorem can safely be applied if n 30 Central Limit Theorem is well approximated by a normal curve even when the population distribution is not normal confidence interval estimate specifies a range of plausible values for a population characteristic confidence level associated with a confidence interval is the success rate of the method used to construct the interval A statistic that is unbiased and has a small standard error is likely to result in an estimate that is close to the actual value of the population characteristic Margin of error a statistic is the maximum likely estimation error It is unusual for an estimate to differ from the actual value of the population characteristic by more than the margin of error Margin of error M solving for n If the sample size is smaller than 10 of population size M is adjusted by finite population correction factor Since this correction factor is always less than 1 the adjusted margin of error will be smaller confidence interval for a population proportion margin of error Interpretation of Confidence Interval You can be 95 confident that the actual value of the population proportion is included in the computed interval Interpretation of 95 Confidence Level A method has been used to produce the confidence interval that is successful in capturing the actual population proportion approximately 95 of the time An alternative to the large sample z interval mod hypotheses are always statements about population characteristics and never about sample statistics Never state a null or alternative hypothesis using sample statistics A hypothesis test uses sample data to choose between two competing hypotheses about a population characteristic If the null hypothesis is not rejected the conclusion is fail to reject y B y y want to imply that you have evidence that the null hypothesis is true P value specifies how likely it is that a sample would be as or more extreme than the one observed if H0 were true Test statistic Knowing the value of the test statistic allows calculation of the corresponding P value Categorical or numerical Number of sample or treatment Question type Study type Estimation Sample Hypothesis Sample Estimation Sample Hypothesis Sample Estimation Sample Numerical variable 1 Hypothesis Sample Numerical variable 1 Estimation Sample Numerical variable 2 Hypothesis Sample Numerical variable Categorical variable Categorical variable Categorical variable Categorical variable Hypothesis Sample Numerical variable Estimation Sample Numerical variable One Sample z Confidence Interval for a Proportion 1 One Sample z Test for a Proportion 1 2 test statistic
View Full Document