The relationship between temperature and the coffee sales is a negative exponential of temperature
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What is relation?</h3>
relation is subject of order between to sets or how the connected to each other.
The temperature of liquid is essential in the process of brewing because its affects the rate of evaporation or extraction. it refers to the test and matters that are dissolved from the coffee beans. The hot is the water, the quick it is to extract. At a high temperature, it’s tougher to control the rate of extraction. This can lead to over-evaporation of liquid, making your coffee taste too bitter since the heat strips away a lot of oxygen.
since the temperature varies over the year, which implies the taste of coffee also vary in a manner that in cold days people love coffees and in hotter days the people love to drink cold drinks instead of coffees
so in cold days the sales of coffees is grater in comparison with hot days
Thus the relationship between the sales of coffees and temperature is negative exponential of temperature.
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Answer:
Step-by-step explanation:
trapezium area
A=a+b/2(h)
Whole: A=8+10/2(6)
A=54 cm
Hole: 5+7/2(3)
a=18
54cm-18cm= 36
area of shaded region is 36cm.
Answer:
Step-by-step explanation:
Joint variations occurs when one variable depends on the value of two or more variables. The variable varies directly or indirectly with the other variables combined together. The other variables are held constant. From the given examples, the equation(s) that represent joint variations are
1) z = 3x/y
z varies directly with x and inversely with y.
2) w = abc/4
w varies inversely with a,b and c. 4 is the value of the constant of variation.
Since you know the area and the width, you can divide the area by the width to find the length. This gives you a length of 110 yards. To find the perimeter of the soccer field, you would add all the side lengths together. Since the width is 70, you would add 70 + 70, along with the length, 110 + 110. This gives you a perimeter of 360.
Answer:
The Normal distribution is a continuous probability distribution with possible values all the reals. Some properties of this distribution are:
Is symmetrical and bell shaped no matter the parameters used. Usually if X is a random variable normally distributed we write this like that:
The two parameters are:
who represent the mean and is on the center of the distribution
who represent the standard deviation
One particular case is the normal standard distribution denoted by:
Example: Usually this distribution is used to model almost all the practical things in the life one of the examples is when we can model the scores of a test. Usually the distribution for this variable is normally distributed and we can find quantiles and probabilities associated
Step-by-step explanation:
The Normal distribution is a continuous probability distribution with possible values all the reals. Some properties of this distribution are:
Is symmetrical and bell shaped no matter the parameters used. Usually if X is a random variable normally distributed we write this like that:
The two parameters are:
who represent the mean and is on the center of the distribution
who represent the standard deviation
One particular case is the normal standard distribution denoted by:
Example: Usually this distribution is used to model almost all the practical things in the life one of the examples is when we can model the scores of a test. Usually the distribution for this variable is normally distributed and we can find quantiles and probabilities associated
