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Alja [10]
2 years ago
5

Given: LP=NP ML=MN Prove: LQ=QN

Mathematics
1 answer:
julsineya [31]2 years ago
4 0

Answer:

The Proof is below.

Step-by-step explanation:

Given:

\overline {LP} \cong \overline{NP}

\overline {ML} \cong \overline{MN}

To Prove:

\overline {LQ} \cong \overline{QN}

Proof:

In  ΔLPM  and ΔNPM  

\overline {LP} \cong \overline{NP}  ……….{Given}

\overline {ML} \cong \overline{MN}  ……….{Given}

\overline {LP} \cong \overline{NP}  ……….{Reflexive Property}

ΔLPM ≅ ΔNPM      ….{ By Side-Side-Side congruence test}

∴ ∠LMP ≅ ∠NMP  ...{Corresponding parts of congruent triangles (c.p.c.t).}.....( 1 )

Now In ΔLMQ  and ΔNMQ  

\overline {ML} \cong \overline{MN}  ……….{Given}

∠LMQ ≅ ∠NMQ                                 ..........{From 1 above}

\overline {MQ} \cong \overline{MQ}  ……….{Reflexive Property}

ΔLMQ ≅ ΔNMQ         ....{ By Side-Angle-Side Congruence test}

∴ \overline {LQ} \cong \overline{QN} ...{Corresponding parts of congruent triangles (c.p.c.t).}.....Proved

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Step-by-step explanation:

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Answer:

Kindly check explanation

Step-by-step explanation:

Given the data:

Temp. 174 176 177 178 178 179 180 181

Ratio 0.86 1.31 1.42 1.01 1.15 1.02 1.00 1.74

Temp. 184 184 184 184 184 185 185 186

Ratio 1.43 1.70 1.57 2.13 2.25 0.76 1.37 0.94

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Using the online linear regression calculator, the lie of best fit which models the data above is :

ŷ = 0.09386X - 15.55523

Where ;

X = independent variable

ŷ = predicted or dependent variable

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0.09386 = gradient / slope

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Point estimate when tank temperature is 186

ŷ = 0.09386(186) - 15.55523

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Residual error (y - ŷ), ŷ = 1.90273 when x = 186

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Answer:

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