Refer to the accompanying data set and construct a 90 % confidence interval estimate of the mean pulse rate of adult females; then do the same for adult males. Compare the results. LOADING... Click the icon to view the pulse rates for adult females and adult males. Construct a 90 % confidence interval of the mean pulse rate for adult females. nothing bpmless than muless thannothing bpm (Round to one decimal place as needed.) Construct a 90 % confidence interval of the mean pulse rate for adult males. nothing bpmless than muless thannothing bpm (Round to one decimal place as needed.) Compare the results. A. The confidence intervals do not overlap, so it appears that there is no significant difference in mean pulse rates between adult females and adult males. B. The confidence intervals overlap, so it appears that there is no significant difference in mean pulse rates between adult females and adult males. C. The confidence intervals overlap, so it appears that adult males have a significantly higher mean pulse rate than adult females. D. The confidence intervals do not overlap, so it appears that adult females have a significantly higher mean pulse rate than adult males. Males Females 87 80 71 96 50 60 60 69 54 59 61 79 53 77 76 85 52 89 62 59 72 37 61 66 63 86 78 75 81 79 66 66 64 65 96 76 41 62 86 63 73 87 61 82 73 72 70 77 52 88 63 92 53 87 79 91 71 90 65 93 63 71 96 89 57 83 66 83 55 72 60 57 66 101 68 71 81 75 59 74
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
Refer to the accompanying data set and construct a
muless thannothing
muless thannothing
Males Females
87 80
71 96
50 60
60 69
54 59
61 79
53 77
76 85
52 89
62 59
72 37
61 66
63 86
78 75
81 79
66 66
64 65
96 76
41 62
86 63
73 87
61 82
73 72
70 77
52 88
63 92
53 87
79 91
71 90
65 93
63 71
96 89
57 83
66 83
55 72
60 57
66 101
68 71
81 75
59 74
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