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3 years ago

Please help :)! the pic gives you everything you need!

Mathematics

1 answer:

velikii [3]3 years ago

8 0

Answer:

use Socratic

Step-by-step explanation:

it's a app

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The tape diagram below represents 100%.

rjkz [21]

Answer:

Step-by-step explanation:

Well the answer is 40 cause you count by 20 so if you in 20 t o times then you would get 40 percent

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3 years ago

Why is it important to avoid a smaller sample size?

Nitella [24]

Answer:The importance of sample size calculation cannot be overemphasized. A research can be conducted for various objectives. A smaller sample will give a result which may not be sufficiently powered to detect a difference between the groups and the study may turn out to be falsely negative leading to a type II error.

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3 years ago

Read 2 more answers

A researcher has developed a new drug designed to reduce blood pressure. In an experiment, 21 subjects were assigned randomly to

Paladinen [302]

Answer:

Step-by-step explanation:

Hello!

The objective of the research is to compare the newly designed drug to reduce blood pressure with the standard drug to test if the new one is more effective.

Two randomly selected groups of subjects where determined, one took the standard drug (1- Control) and the second one took the new drug (2-New)

1. Control

X₁: Reduction of the blood pressure of a subject that took the standard drug.

n₁= 23

X[bar]= 18.52

S= 7.15

2. New

X₂: Reduction of the blood pressure of a subject that took the newly designed drug.

n₂= 21

X[bar]₂= 23.48

S₂= 8.01

The parameter of study is the difference between the two population means (no order is specified, I'll use New-Standard) μ₂ - μ₁

Assuming both variables have a normal distribution, there are two options to estimate the difference between the two means using a 95% CI.

1) The population variances are unknown and equal:

[(X[bar]₂-X[bar]₁)± $t_{n_1+n_2-2;1-\alpha /2}$ *( $Sa\sqrt{\frac{1}{n_1} +\frac{1}{n_2} }$ )]

$t_{n_1+n_2-2;1-\alpha /2}= t_{23+21-2;1-0.025}= t_{42;0.975}= 2.018$

$Sa=\sqrt{\frac{(n_1-1)*S_1^2+(n_2-1)S_2^2}{n_1+n_2-2} } = \sqrt{\frac{22*7.15^2+20*8.01^2}{42} }= 7.57$

[23.48-18.52]±2.018*( $7.57*\sqrt{\frac{1}{21} +\frac{1}{23} }$ )]

[0.349; 9.571]

2) The population variables are unknown and different:

Welche's approximation:

[(X[bar]₂-X[bar]₁)± $t_{Dfw;1-\alpha /2}$ *( $\sqrt{\frac{S_1^2}{n_1} +\frac{S_2^2}{n_2} }$ )]

$Df_{w}= \frac{(\frac{S_1^2}{n_1} +\frac{S^2_2}{n_2} )^2}{\frac{(\frac{S_1^2}{n_1} )^2}{n_1-1}+ \frac{(\frac{S_2^2}{n_2} )^2}{n_2-1} } = \frac{(\frac{7.15^2}{23} +\frac{8.01^2_2}{21} )^2}{\frac{(\frac{7.15^2}{21} )^2}{20}+ \frac{(\frac{8.01^2}{23} )^2}{22} } = 42.85= 42$