Confidence Interval

units
abc
abc
abc
vector
logic
function
standard

abc

↵

(

)

↑

←

↓

→

units
abc
abc
abc
vector
logic
function
standard

shift

greek

↵

(

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↑

←

↓

→

units
abc
abc
abc
vector
logic
function
standard

shift

greek

↵

(

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↑

←

↓

→

units
abc
abc
abc
vector
logic
function
standard

−

×∗×

√

a■

{......

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]

∞

{}

det

(m×n)

↵

(

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↑

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→

units
abc
abc
abc
vector
logic
function
standard

∧

⊥

∀

⊢

∅

∪

⊂

∨

⊤

∃

≠

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∈

∩

⊆

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⇒

⊬

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⊭

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(

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↑

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→

units
abc
abc
abc
vector
logic
function
standard

−

×∗×

√

a■

log

sin

[

]

cos

lim

∞

[

)

≥

tan

(

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arc

{......

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(

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→

units
abc
abc
abc
vector
logic
function
standard

−

×∗×

√

a■

log

sin

∧

cos

∨

≥

tan

all

≤

none

↵

(

)

↑

←

↓

→

units
abc
abc
abc
vector
logic
function
standard

°C

mol

bar

units

↵

(

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↑

←

↓

→

units
abc
abc
abc
vector
logic
function
standard

−

×∗×

√

a■

log

sin

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cos

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all

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none

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(

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The municipality of Amsterdam wants to estimate the average water retention capacity of the green roofs, by taking a simple random sample of size #30# from the population. Simulate what happens in this case by taking a simple random sample from the variable capaciteit in the dataset V (groene daken). Use the seed: #52# by applying the command set.seed(52) before running the sample() command.

What is the average of your sample?

#\bar{X} = #

#mm#

6. Parameter Estimation and Confidence Intervals: Practical 6

Confidence Interval