Answer:
B would be a *dependent* event, and A would be an *independent* event.
Step-by-step explanation:
Independent events are separate events where the outcome in either event does not affect the other's probability. The opposite, where the outcome of the one event affects the other's probably, is dependent.
For Option A, taking a tile out and then replacing it does not affect the probability that the same tile will be picked for the 2nd picking.
For Option B, taking a tile out of the bag and then picking another tile are 2 separate events and both have different probabilities for picking identical tiles.
Therefore, Option B is dependent and Option A is independent.
Answer:
The third one. The square in the top left can only fold to the right or down.... which means there is guaranteed to be an open side remaining on the square.
Answer:
Complete the following statements. In general, 50% of the values in a data set lie at or below the median. 75% of the values in a data set lie at or below the third quartile (Q3). If a sample consists of 500 test scores, of them 0.5*500 = 250 would be at or below the median. If a sample consists of 500 test scores, of them 0.75*500 = 375 would be at or above the first quartile (Q1).
Step-by-step explanation:
The median separates the upper half from the lower half of a set. So 50% of the values in a data set lie at or below the median, and 50% lie at or above the median.
The first quartile(Q1) separates the lower 25% from the upper 75% of a set. So 25% of the values in a data set lie at or below the first quartile, and 75% of the values in a data set lie at or above the first quartile.
The third quartile(Q3) separates the lower 75% from the upper 25% of a set. So 75% of the values in a data set lie at or below the third quartile, and 25% of the values in a data set lie at or the third quartile.
The answer is:
Complete the following statements. In general, 50% of the values in a data set lie at or below the median. 75% of the values in a data set lie at or below the third quartile (Q3). If a sample consists of 500 test scores, of them 0.5*500 = 250 would be at or below the median. If a sample consists of 500 test scores, of them 0.75*500 = 375 would be at or above the first quartile (Q1).
The domain is the x-axis and the range is the y-axis.
So the range of the function would be the Y values given.
So the range would be (3, 6, 9, 12, 15).