require(mosaic)
a) TRUE
b) TRUE
a) Quantile, 65
qnorm(0.01, mean = 100, sd = 15)
## [1] 65.1
b) Quantile
c) Left end of interval: 90
Right end of interval: 110
qnorm(c(0.25, 0.75), mean = 100, sd = 15)
[1] 89.88 110.12
d) Left end of interval: 81
Right end of interval: 119
qnorm(c(0.1, 0.9), mean = 100, sd = 15)
[1] 80.78 119.22
e) 0.41
pnorm(120, mean = 100, sd = 15)
[1] 0.9088
pnorm(100, mean = 100, sd = 15)
[1] 0.5
0.9087888 - 0.5
[1] 0.4088
a) Min & Max
b) Mean & Standard Deviation
c) Average Number per Interval
d) Average Number per Interval
e) Probability and Size
a) Binomial
b) Normal
c) Binomial
a) It is binomial.
b) It's not for both of the above reasons.
c) It's not because the probability is not fixed for every individual component. (Eftersom vi inte vet storleken på meningarna.)
d) It is binomial.
e) It is binomial.
f) It's not because the sample size is not fixed.
g) It is binomial. Beroende på hur lotteriet är utformat.
a) point.estimate
b) margin.of.error
c) confidence.level
a) C
b) B
B
1. Point estimate: 9.19 Margin of error: 0.211
feet = fetchData("kidsfeet.csv")
Retrieving from http://www.mosaic-web.org/go/datasets/kidsfeet.csv
mean(width ~ sex, data = feet)
B G
9.190 8.784
summary(lm(width ~ sex, data = feet))
Call:
lm(formula = width ~ sex, data = feet)
Residuals:
Min 1Q Median 3Q Max
-0.8842 -0.2900 0.0158 0.4600 0.7158
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 9.190 0.106 86.97 <2e-16 ***
sexG -0.406 0.151 -2.68 0.011 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.473 on 37 degrees of freedom
Multiple R-squared: 0.163, Adjusted R-squared: 0.14
F-statistic: 7.18 on 1 and 37 DF, p-value: 0.0109
0.1057 * 2
[1] 0.2114
2. Point estimate: 8.99 Margin of error: 0.16
mean(width, data = feet)
[1] 8.992
summary(lm(width ~ 1, data = feet))
Call:
lm(formula = width ~ 1, data = feet)
Residuals:
Min 1Q Median 3Q Max
-1.0923 -0.3423 0.0077 0.3577 0.8077
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 8.9923 0.0816 110 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.51 on 38 degrees of freedom
0.0816 * 2
[1] 0.1632
3. Point estimate: 0.406 Margin of error: 0.30
summary(lm(width ~ sex, data = feet))
Call:
lm(formula = width ~ sex, data = feet)
Residuals:
Min 1Q Median 3Q Max
-0.8842 -0.2900 0.0158 0.4600 0.7158
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 9.190 0.106 86.97 <2e-16 ***
sexG -0.406 0.151 -2.68 0.011 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.473 on 37 degrees of freedom
Multiple R-squared: 0.163, Adjusted R-squared: 0.14
F-statistic: 7.18 on 1 and 37 DF, p-value: 0.0109
0.1514 * 2
[1] 0.3028