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3 years ago

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Prove that the median to the base of an isosceles triangle is also: the altitude to the base.

2 answers:

EleoNora [17]3 years ago

7 0

Hey there!

The base angles theorem converse states if two angles in a triangle are congruent, then the sides opposite those angles are also congruent. The Isosceles Triangle Theorem states that the perpendicular bisector of the base of an isosceles triangle is also the angle bisector of the vertex angle.

Let me know if you are still confused and need a better explination :)

Have a great day!

kondor19780726 [428]3 years ago

4 0

Answer:

The base angles theorem converse states if two angles in a triangle are congruent, then the sides opposite those angles are also congruent. The Isosceles Triangle Theorem states that the perpendicular bisector of the base of an isosceles triangle is also the angle bisector of the vertex angle. Let me know if you are still confused and need a better explanation :) Have a great day!

Step-by-step explanation:

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A number d minus 2 is less than -1 ?

tamaranim1 [39]

d - 2 < -1 is how this inequality would be displayed.

However, we can solve for the value of d by treating this like a standard algebraic equation.

d - 2 < -1

<em><u>Add 2 to both sides.</u></em>

d < 1

The value of d is less than 1.

Let me know if you have any other questions.

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2 years ago

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A researcher collected data on the hours of TV watched per day from a sample of five people of different ages. Here are the resu

frozen [14]

Answer:

1. The least squares regression is y = -0.1015·x + 6.51

2. The independent variable is b) age

Please see attached table

Step-by-step explanation:

The least squares regression formula is given as follows;

$\dfrac{\sum_{i = 1}^{n}(x_{i} - \bar{x})\times \left (y_{i} - \bar{y} \right ) }{\sum_{i = 1}^{n}(x_{i} - \bar{x})^{2}}$

We have;

$\bar x$ = 24

$\bar y$ = 4

$\Sigma (x_i - \bar x) (y_i - \bar y)$ = -79

$\Sigma (x_i - \bar x)^2$ = 778

$\therefore \hat \beta =\dfrac{\sum_{i = 1}^{n}(x_{i} - \bar{x})\times \left (y_{i} - \bar{y} \right ) }{\sum_{i = 1}^{n}(x_{i} - \bar{x})^{2}} = \frac{-79}{778} = -0.1015$

The least squares regression is y = -0.1015·x + α

∴ α = y -0.1015·x = 6 - (-0.1015 × 5) = 6.51

The least squares regression is thus;

y = -0.1015·x + 6.51

2. The independent variable is the age b)

3. Steps to create an ANOVA table with α = 0.05

The overall mean = (43 + 30 + 22 + 20 + 5 + 1 + 6 + 4 + 3 + 6 )/10 = 14

There are 2 different treatment = $df_{treat} = 2 - 1 = 1$

There are 10 different treatment measurement = $df_{tot} = 10 - 1 = 9$

$df_{res} = 9 - 1 = 8$

$df_{treat} + df_{res} = df_{tot}$

The estimated effects are;

$\hat A_1 = 24 - 14 = 10$

$\hat A_2 = 4 - 14 = -10$

$SS_{treat} = 10^2 \times 5 + (-10)^2 \times 5 =1000$

$\sum_{i}\SS_{row}_i = \sum_{i}\sum_{j} (y_{ij} - \bar y)= [(1 - 4)^2 + (6 - 4)^2 + (4 - 4)^2 + (3 - 4)^2 + (6 - 4)^2] = 18$

$\sum_{i} S S_{row}_i = \sum_{i}\sum_{j} (y_{ij} - \bar y) ^2= [(43 - 24)^2 + (30 - 24)^2 + (22 - 24)^2 + (20 - 24)^2 + (5 - 24)^2] = 778$

$S S_{res} = \sum_{i} S S_{row}_i = 778 + 18 = 796$

$SS_{tot}$ = (43 - 14)² + (30 - 14)² + (22 - 14)² + (20 - 14)² + (5 - 14)² + (1 - 14)1² + (6 - 4 )² + (3 - 14)² + (6 - 14)² = 1796

$MS_{treat} = \dfrac{SS_{treat} }{df_{treat} } = \dfrac{1000}{1} = 1000$

$MS_{res} = \dfrac{SS_{res} }{df_{res} } = \dfrac{796}{8} = 99.5$

F- value is given by the relation;

$F = \dfrac{MS_{treat} }{MS_{res} } = \frac{1000}{99.5} = 10.05$

We then look for the critical values at degrees of freedom 1 and 8 at α = 0.05 on the F-distribution tables 5.3177

Hence; $F = 10.05 > F_{1,8}^{Krit}(5\%) = 5.3177$ , we reject the null hypothesis.

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2 years ago

Hey there whats 1-100-100-1223-1030 :)

grigory [225]

Answer:

don't know

Step-by-step explanation:

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Jennie said you plus me sadly could be dangerous

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2 years ago

Adam drafts a tractor on a scale drawing. The drawing scale is 2 inches for each foot. If the drawing is 29 inches long, how lon

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Answer:

58 feet

Step-by-step explanation:

2 inches per foot

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3 years ago

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