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sattari [20]
1 year ago
9

when is the population standard deviation greater than the population variance? a. when the variance is less than 1 b. when the

variance is greater than 1 c. when the variance is negative d. the standard deviation is never greater than the variance.
Mathematics
1 answer:
LenKa [72]1 year ago
7 0

The population standard deviation is greater than the population variance when A. when the variance is less than 1

<h3>What is standard of deviation?</h3>

A population's standard deviation is calculated by taking the square root of the data set's variance. It is employed to compute a confidence interval for making judgments (such as accepting or rejecting a hypothesis). Sample standard deviation is a slightly more complicated computation.

Variability is measured by the variance. The average of the squared deviations from the mean is used to calculate it. Variance tells you the degree of spread in your data set. The variance is greater in respect to the mean when the data are more dispersed.

Learn more about variance on:

brainly.com/question/15858152

#SPJ1

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Answer:

Yes, the average speed for the entire trip from A to C is equal to 80\frac{km}{h}

Step-by-step explanation:

The average speed of an object is defined as the distance traveled divided by the time elapsed. Velocity is a vector quantity, and average velocity can be defined as the displacement divided by the time. For the special case of straight line motion in the x direction, the average velocity takes the form:

V_a_v_e_r_a_g_e=\frac{x_2-x_1}{t_2-t_1}=\frac{Δx}{Δt}

If the beginning and ending velocities for the motion are known, and the acceleration is constant, the average velocity can also be expressed as:

V_a_v_e_r_a_g_e=\frac{V_1+V_2}{2}

We Know that:

V_1=70\frac{km}{h} \\\\V_2=90\frac{km}{h}

Replacing the values:

V_a_v_e_r_a_g_e=\frac{70+90}{2} =\frac{160}{2}=80\frac{km}{h}

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4 3/10 divided by 3/5
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7.16

Step-by-step explanation:

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Greg needs $51 to go on a field trip. He has saved $12.75. He earns $6.50 per hour cleaning his neighbor's garden, and he earns
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Assume V and W are​ finite-dimensional vector spaces and T is a linear transformation from V to​ W, T: Upper V right arrow Upper
scZoUnD [109]

Answer:

Thus for the vectors v_1, v_2, v_p there are scalars c_1, c_2, c_p not all zeros, such that c_1v_1 +c_2v_2+... +c_pv_p = 0. It means that the vectors v_1, v_2, v_p are linearly dependent in contradiction with the fact that the vectors form a basis for H. So the assumption that T(v_1), T(v_2),..., T(v_p) are linearly dependent is false, proving the required.  

Step-by-step explanation:

Let B = {v_1 ,v_2,..., v_p} be a basis of H, that is dim H = p and for any v ∈ H there are scalars c_1 , c_2, c_p, such that v = c_1*v_1 + c_2*v_2 +....+ C_p*V_p It follows that  

T(v) = T(c_1*v_1 + c_2v_2 + ••• + c_pV_p) = c_1T(v_1) +c_2T(v_2) + c_pT(v_p)

so T(H) is spanned by p vectors T(v_1),T(v_2), T(v_p). It is enough to prove that these vectors are linearly independent. It will imply that the vectors form a basis of T(H), and thus dim T(H) = p = dim H.  

Assume in contrary that T(v_1 ), T(v_2), T(v_p) are linearly dependent, that is there are scalars c_1, c_2, c_p not all zeros, such that  

c_1T(v_1) + c_2T(v_2) +.... + c_pT(v_p) = 0

T(c_1v_1) + T(c_2v_2) +.... + T(c_pv_p) = 0

T(c_1v_1+ c_2v_2 ... c_pv_p) = 0  

But also T(0) = 0 and since T is one-to-one, it follows that c_1v_1 + c_2v_2 +.... + c_pv_p = O.

Thus for the vectors v_1, v_2, v_p there are scalars c_1, c_2, c_p not all zeros, such that c_1v_1 +c_2v_2+... +c_pv_p = 0. It means that the vectors v_1, v_2, v_p are linearly dependent in contradiction with the fact that the vectors form a basis for H. So the assumption that T(v_1), T(v_2),..., T(v_p) are linearly dependent is false, proving the required.  

8 0
3 years ago
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