someone answer this
The residuals in regression estimation are estimates of error. Most commonly, the errors are assumed to be statistically independent, identically distributed and normally distributed, that is, to have a Gaussian distribution.If these were the assumptions under which the regression was calculated then the residuals could (at least potentially) be examined for any departures from the assumptions. Usually they are plotted against the independent variable to see if there is any systematic relationship between the two sets of values. The residuals might also be tested for normality.It's worth reading more about this subject.
None of these could represent anything!
RangeThe term for the difference between the smallest and the largest values in a set of data is called the range. It is probably derived from the idea that the values of the numbers in the data could range anywhere from the lowest to the highest values but not beyond. The range is a measure of how disperse (spread out) the values are but it is not a very powerful measure.
The number between 1 and 11 could refer to several values, depending on the context. If you're looking for a single number, it could be 6, which is the midpoint. However, any integer from 2 to 10 is also a valid answer as they all fall between 1 and 11.
The relationship between the input and output values can be determined by a mathematical function or rule. In this case, when the input is 1 and the output is 8, the rule could be represented as f(x) = 8x, where f(x) is the function and x is the input value. This means that the output is obtained by multiplying the input value (1) by 8.
How could the relationship between Pip and Biddy be described?
the relationship would fail...
The error between the two values in the calculation could be caused by inaccuracies in measurement, rounding errors, or mistakes in the calculation process.
The residuals in regression estimation are estimates of error. Most commonly, the errors are assumed to be statistically independent, identically distributed and normally distributed, that is, to have a Gaussian distribution.If these were the assumptions under which the regression was calculated then the residuals could (at least potentially) be examined for any departures from the assumptions. Usually they are plotted against the independent variable to see if there is any systematic relationship between the two sets of values. The residuals might also be tested for normality.It's worth reading more about this subject.
how is the relationship between jess and his father
The term relationship refers to the personal interaction between one or more people. This could be a one-on-one interaction, as in a romantic relationship, or a family situation, i.e. the relationship between parents and their children. It could also refer to relationships between friends, which could be different depending on the separate groups of friends involved. It could also refer to the connection between humans and their domestic animals, or to the connection between animals themselves.
None of these could represent anything!
The expression "0.6 to 1.4" typically represents a range or ratio, indicating a relationship between the two numbers. In this context, it could signify that for every 0.6 units of one quantity, there are 1.4 units of another. If considering it as a ratio, it can be simplified to a fraction of 3:7. Overall, it highlights a proportional relationship between the two values.
The relationship between a and b can vary depending on the context. It could be a mathematical relationship, a cause-and-effect relationship, a correlation, or a connection in some other way. The specific nature of the relationship would need to be specified for a more precise answer.
There is no actual relationship between the two of you. Anything could happen. At 13 I wouldn't worry about it.
A committed relationship could simply be an agreement between two people. Marriage is a legally binding arrangement, licensed by the state.
I believe that this would probably be a line graph, or a double line graph-whichever you choose to call it. It could also be a double bar graph though too.