Show on an a graph of the aggregate economy the impact of the following on the economic indicators.  The economy produces a level of output below potential GDP. Firms lose confidence in the future direction of the U.S. economy. The AD function [ad]. The AS function [as]. Impact on: real GDP [rgdp] price level [price] unemployment [unemp] State of the economy [state]

Which of the following pseudocode statements says if number is not between 5 and 10 (inclusive):

Given the following code:class LightCycle: def __init__ ( self, rider, type = “light cycle” ): self.rider = rider self.type = type def race ( self, speed, distance ): return “{} {} raced at {} mph for {} miles.”.format (self.rider, self.type, speed, distance )tron_cycle = LightCycle ( “Tron” )result = tron_cycle.race ( 200, 10 )print ( result )What output is printed to the screen?

Which of the following function definitions is correct, considering that required parameters must come before optional parameters?

The len() function can be used to determine the number of items in a list.

Given the following code:transformers = []transformers.append (“Optimus Prime”)transformers.append (“Megatron”)transformers.append (“Hot Rod”)transformers.append (“Starscream”)transformers.append (“Jazz”)transformers.append (“Soundwave”)transformers.append (“Ultra Magnus”)transformers [1] = “Galvatron”del transformers [3]transformers.append (“Bumblebee”)transformers.insert (5, “Wheeljack”)transformers = transformers [:5]transformers.sort ()extra_transformer = transformers [2]transformers [2] = transformers [3]transformers [3] = extra_transformertransformers.pop ()What is the value of the following expression:transformers [2]

Given the following code:numbers = [ 1, 2, 3, 4, 5 ]print (calculateAverageValue (numbers))def calculateAverageValue (items):   num_items = len (items)   average = 0   total = 0   for item in items:     total = total + item     average = total / num_items   return averageWhat is printed to the screen?

A “for” loop can iterate over a list of items in Python.

Given the following code:data = [ 9.3, 2.6, 1.7, 4 ]Which expression will successfully create a Pandas Series from the data?

Given the following code:import numpy as npmy_array = np.array ( [10, 20, 30, 40 ] )total = my_array.sum ()What is the value of the following expression:total