1) Classify the following attributes as binary, discrete, or continuous. Also classify them as qualitative (nominal or ordinal) or quantitative (interval or ratio). Some cases may have more than one interpretation, so briefly indicate your reasoning if you think there may be some ambiguity.
Example: Age in years.
Discrete, quantitative, ratio
a) Time in terms of AM or PM.
b) Brightness as measured by a light meter.
c) Brightness as measured by people's judgments.
d) Angles as measured in degrees between 0 and 360.
e) Bronze, Silver, and Gold medals as awarded at the Olympics.
f) Height above sea level.

a) Time in terms of AM or PM: Binary, qualitative and nominal (binary attributes are considered nominal)

b) Brightness as measured by a light meter: Ratio, quantitative and continuous.

c) Brightness as measured by people's judgments: Discrete, qualitative and ordinal (assuming they're chosen discretely)

d) Angles as measured in degrees between 0 and 360: Ratio, quantitative and continuous.

e) Bronze, Silver, and Gold medals as awarded at the Olympics: Qualitative, discrete and ordinal.

f) Height above sea level: Quantitative, continuous, ratio/interval (depending if it's seen as an arbitrary origin).

the height of the surface increases from the center out to the sides of the road.

step-by-step explanation:

as we move out we move away from the x-axis.

and as mentioned in the problem statement that height of a road increases when we move away from the center x.

hence proved that 3rd option

the height of the surface increases from the center out to the sides of the road.

is the correct option.

55.44 inches

step-by-step explanation:

part a. assuming a perfectly linear relationship, we can find the slope from the first two data points.

slope = m = (change in rainfall)/(change in years)

= (61.80 -62.33)/(2005 -2004) = -0.53/1 = -0.53

then the point-slope form of the equation of the line can be written as

y = m(x -h) +k . . . . . m = -0.53, (h, k) = (0, 62.33)

y = -0.53x +62.33 . . . x = years after 2004

part b. in 2017, x = 2017 -2004 = 13. then the predicted rainfall is

y = -0.53·13 +62.33 = 55.44 . . inches

the predicted rainfall in 2017 is 55.44 in.