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When there are no identifiable trends in a graph it means there is no relationship between the two variables?
Wiki User
∙ 7y ago
Not necessarily. It could be that the domain and range of the variables is not sufficiently large. For example, if you plotted the ages and heights of boys in a school class you would probably find no identifiable trend. But that is not because there is no relationship between age and height, but simply the fact that the age range is very limited.
With time series data there is also a risk of aliasing. To take rather a contrived example, suppose you have a pendulum with a period of t seconds and you make observations about its location every 3t seconds. You will find that the location remains the same! That does not mean that there is no relationship between time and the position of a pendulum.
Wiki User
∙ 7y ago
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Why is it a good idea to make a graph of the data in the data table?
Viewing the data is an easy way to see some of their characteristics such as trends, seasonality, outliers, relationship between variables (linear, quadratic, power etc).
Why would you use a pie graph instead of a line graph?
pie graphs show volume and are good for showing the relationship of size. line graphs are good for showing trends which can lead to predictions.
Description of trends and patterns in the data?
Trends and patterns in the data are social. Data goes in a social patterns.
Does a pie chart in excel compare distinct unrelated objects or trends?
Pie charts are not normally used for trends.
Patterns in results?
They could be trends.
What does it mean when a graph has no identifiable trends?
there is a strong relationship between the variables
When there are no identifiable trends in a graph it most likely means that there is no relationship between the two variables?
there is no solution
When a graph shows no identifiable trends what does it mean?
THere is no solution
What are the vegetation trends of your area?
Answer is What is the relationship between climate change and vegetation trends in my area?
What does no trend mean?
Usually the expression is employed in the context of the relationship between a dependent variable and another variable. The latter may or may not be independent: often it is time but that is not necessary. In some cases there is some indication that that there is a linear relationship between the two variables and that relationship is referred to as a trend.Note that a trend is not the same as causation. There may appear to be a strong linear trend between two variables but the variables may not be directly related at all: they may both be related to a third variable. Also, the absence of linear trends does not imply that the variables are unrelated: there may be non-linear relationships.
What type of graph shows no identifiable trends?
every thing does that silly
What does it most likely mean if a graph shows no identifiable trends?
No Solution!
Why is it a good idea to make a graph of the data in the data table?
Viewing the data is an easy way to see some of their characteristics such as trends, seasonality, outliers, relationship between variables (linear, quadratic, power etc).
Does the graph have no use or value if it shows no identifiable trends?
no it still identifies highs and lows
How do you read a scattergram?
To read a scattergram, observe how the data points are dispersed on the graph. Look for any patterns or trends, such as a positive or negative correlation. Assess how closely the points cluster around a line or show a particular shape, which can indicate the strength and direction of the relationship between the variables.
What is the best way in SPSS to find out the strength of the relationship between the financial trends of a bank and the industry using financial statement items?
The best way in SPSS to find out the strength of the relationship between the financial trends of a bank and the industry using financial statement items is to use the determinants of Bank Profitability.
What are 2 things that line graphs allow scientiest to do?
Allows scientists to..... 1. Make predictions 2. Correlate relationships between variables 3. Show trends and patterns
