Answer: Hello mate!
We know that you have a graph of y vs t, and we know that this is an "altitude" graph.
Then we can assume that the y represents the altitude, and t represents the time, and this graph shows the altitude of something as a function of the time.
the t-intercept means that the graph passes through the y-axis, this means that, in this point, y is equal to zero:
Then, at the t-intercept, we have y = 0, which means that at this time (where is the intersection) the altitude is equal to zero.
The y-intercept means that the graph passes through the y-axis, where t = 0
this is the initial value of the altitude, where t = 0 usually denotes the time where we start to measure.
Answer:
$3,153.32
Step-by-step explanation:
Given that
The deposited amount is $3,000
The annual interest rate is 1.25%
So, the semi-annual interest rate is 1.25% ÷2 = 0.625%
And, the time period = 4 × 2 = 8
We need to find out the final balance
So,
As we know that
Future value = Present value × (1 + rate of interest)^number of years
= $3,000 × (1 + 0.625%)^8
= $3,153.32
Answer:
(1.4), because both lines pass through this point
Step-by-step explanation:
Answer:
Inference for Regression
Step-by-step explanation:
Let us try to understand the difference between each of them.
1) Two sample t- test : the following assumptions must be used while applying the t- tests.
- The samples of n observations X₁,X₂,X₃,...........X n is selected randomly.
- The population from which the small sample is drawn is normal.This is essential for X` and s , the two components of the statistics t, to be independent. it has , however been shown that slight departures from normality do not seriously effect the tests.
- <em>In case of two small samples both the samples are selected randomly , both the populations are normal and both the populations have equal variances.</em>
2) Chi - squared Test for independence:
The two attributes A and B are said to be independent if the actual frequency equals the expected one , that is, if (AB) = (A)(B)/ N
Similarly α and β will be independent is (αβ) = ( α)( β)/ N and so on.
3) Inference for Regression
When both X and Y are observed at random i.e the sample values are from a bi variate population there are two regression equations , each obtained by choosing that variable as dependent whose average value is to be estimated and treating the other variable as independent .
4) A N O V A
The various sources of variation , degrees of freedom , the sum of squares and the mean squares associated with the sources are generally shown in a table called analysis of variance table or A N O V A table.
5) Matched pairs
It can be used when the experiment has only two events or possibilities and each variable can be grouped in either of the two conditions. Example people having C O V I D 19 and not having C O V I D 19.
