Answer:
c. 3 / 13
d. 2 / 13
Step-by-step explanation:
c.
A deck of cards has 52 cards. There are cards of 4 suits- Spades, Hearts, Diamonds and Clubs.
So, there are 52/4= 13 cards of each suit.
Among these 13 cards, there are 3 picture cards or face cards as they are called. These are the Jack, Queen and King cards.
So, the number of total picture cards = 4*3 = 12
the number of cards are 52
theoretical probability formula: P = favorable events/ possible events
P = 12 / 52
P = 3 / 13
d.
there are four aces and four sevens in the deck
so favorable events = 4 + 4 = 8
possible eventas = 52
P = 8 / 52
P = 2 / 13
Answer : Hershel buys 2 bags of fruit snacks.
Explanation :
Since we have given that
Number of bags of granola =3
Number of bags of cookies = 5
Total number of bags he buys from the bake sale =10
So, number of bags of fruit snacks = 2
Hence, Hershel buys 2 bags of fruit snacks .
It is a comparison type of word problem.
As we just compare the items with the total items to get the remaining items.
Answer:
6x > x + 20,
x > 4
or
X belongs to a set of real numbers [0, +infinity)
Step-by-step explanation:
6x > x + 20
5x > 20
x > 4
Answer:
35
Step-by-step explanation:
Answer:
<h3>
The Option B) Multiple regression is correct</h3><h3>Regression analysis involving one dependent variable and more than one independent variable is known as <u>multiple regression.</u></h3>
Step-by-step explanation:
Given that regression analysis involving one dependent variable and more than one independent variable
For : Regression analysis involving one dependent variable and more than one independent variable is known as <u>multiple regression</u>
- In statistics, a linear regression is a linear relationship between a dependent variable and one or more independent variables.
- In statistics for more than one independent variable and with one dependent variable in regression analysis , then the regression is called as multiple regression.
- Therefore Option B) Multiple regression is correct
<h3>Regression analysis involving one dependent variable and more than one independent variable is known as <u>
multiple regression</u>.</h3>
