Categorical data may or may not have some logical order
while the values of a quantitative variable can be ordered and
measured.
Categorical data examples are: race, sex, age group, and
educational level
Quantitative data examples are: heights of players on a
football team; number of cars in each row of a parking lot
a) Colors of phone cover - quantitative
b) Weight of different phones - quantitative
c) Types of dogs - categorical
d) Temperatures in the U.S. cities - quantitative
Step-by-step explanation:
Total distance covered=distance covered by walking+distance covered by jogging
=6/7+4/5=30+28/35
=58/35miles
How much farther did you walk than jog
=6/7-4/5
=30-28/35
=2/35miles
Answer:
24
Step-by-step explanation:
i quessed
Use the fact that 1 axe head = 3.20 trade value.
Let N denote number of axe heads needed to trade for a trade gun.
3.20×N=120.00
》 N=120/3.2 which will give number of axe heads needed. Round to the nearest ones place if you must.
Answer:
A customer who sends 78 messages per day would be at 99.38th percentile.
Step-by-step explanation:
Normal Probability Distribution:
Problems of normal distributions can be solved using the z-score formula.
In a set with mean
and standard deviation
, the z-score of a measure X is given by:

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the p-value, we get the probability that the value of the measure is greater than X.
Average of 48 texts per day with a standard deviation of 12.
This means that 
a. A customer who sends 78 messages per day would correspond to what percentile?
The percentile is the p-value of Z when X = 78. So



has a p-value of 0.9938.
0.9938*100% = 99.38%.
A customer who sends 78 messages per day would be at 99.38th percentile.