Answer:
convex lens
Explanation:
An image is form in retina with light rays converging most at cornea and upon entering and existing the lens.Rays from top and bottom of the object are traced and produce an inverted image on the retina
Answer:
1.2 kg
Explanation:
Let UP ramp be the positive direction
F = ma
T - Wt || - Ff = m(0)
mg - Μgsinθ - μΜgcosθ = 0
m(9.8) - 13sin35 - 0.36(13)cos35 = 0
m = 13(sin35 + 0.36cos35) / 9.8
m = 1.15205... ≈ 1.2 kg
P₄ + 3O₂ ⟶ 2P₂O₃
Explanation:
A balanced equation is any equation that complies with the law of conservation of matter and mass.
The law of conservation of matter states that "in a chemical reaction, matter is neither created nor destroyed but simply rearranges. ".
This suggests that the total number of atoms on both reactant and product sides must be the same in a balanced chemical equation. Also, the same atoms are found on both sides of a chemical equation with no additional or external species.
Now let us check if the equation is conserved:
P₄ + 3O₂ ⟶ 2P₂O₃
Atoms reactant product
P 4 4
O 6 6
We see that we have equal number of atoms on both sides. The equation is balanced.
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The dinosaurs first appeared in the Mesozoic and the first mass extinction occurred during the Paleozoic. Moreover, humans first appeared in the Cenozoic.
<h3>The geological eras and biological events</h3>
The dinosaurs emerged during the Triassic Period of the Mesozoic Era, approximately 220-225 million years ago.
The first mass extinction occurred in the Ordovician Period (the second period of the Paleozoic Era).
The Cenozoic is the current geological Era that encompasses the last 60 million years.
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The difference between the observed points and the regression line points is equal to the correlation.
The strength and direction of a relationship between two or more variables are described by the statistical measure of correlation, which is given as a number. However, a correlation between two variables does not necessarily imply that a change in one variable is the reason for a change in the values of the other.
Regression expresses the relationship as an equation, whereas correlation assesses the strength of the linear link between two variables. The square of the correlation coefficient, also known as Pearson's r, between the observed and predicted values in a regression is sometimes referred to as R2.
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