Scatter graphs are best.
Line graphs are OK if the trend is linear but not much good if the trend is non-linear.
observe general trends in the data. its from a castle learning.
Line graphs are used to display data or information that changes continuously over time. Line graphs allow us to see overall trends such as an increase or decrease in data over time.By contrast, bar graphs emphasize the magnitude of changes, so they are an excellent way to demonstrate data with sharp fluctuations, but not continuously over time.
A line graph should not be used when the data does not represent continuous trends, such as categorical data or discrete values that don't have an inherent order. Additionally, if the dataset contains too many variables or data points, it can become cluttered and difficult to interpret. Lastly, line graphs are inappropriate for showcasing relationships in data that require comparison of distinct groups or categories rather than trends over time.
To summarise data and present them in a form that are more easily understood.
http://socrates.bmcc.cuny.edu/cpe/circle_pie.html
Observe general trends in the data
trends
observe general trends in the data. its from a castle learning.
The way you can use graphs of polynomial functions to show trends in data is by comparing results between different functions. The alternation between the data will show the trends. Time can also be used to show the amount of variation.
Graphs are used to investigate the relationships and trends of the data collected. It is easier to see a pattern in a graph than a table of data.
to make the observed data more accurateF*CK THAT FIRST ANSWER its to observe general trends in the data i got the fricen question wrong on a test cuz i used the first answer :(
Yes, you can graph quantitative observations, as they represent numerical data that can be visualized. Common types of graphs used for this purpose include bar graphs, line graphs, and scatter plots, which effectively display relationships and trends within the data. By plotting quantitative observations on these graphs, you can easily interpret and analyze patterns or variations in the data set.
Data from an interval scale can be effectively represented using line graphs, bar graphs, and histograms. Line graphs are particularly useful for displaying trends over time, while bar graphs can compare different categories. Histograms are ideal for showing the distribution of continuous data. Each of these graph types allows for meaningful interpretation of interval data, highlighting relationships and patterns.
graphs are to compare and contrast data
Scatter graphs. Line graphs may be used at a later stage when there is a better idea of the general shape of the line - whether it is a straight line, a quadratic curve, a logarithmic or exponential curve etc, or one of the standard probability distributions.
The graph that is most used for categorical data is the pie chart. Bar graphs have also been used for categorical data.
Spreadsheets and graphs are closely related tools used for data analysis and visualization. Spreadsheets, such as Microsoft Excel or Google Sheets, allow users to organize, calculate, and manipulate data in tabular form. Graphs, or charts, are visual representations of this data, making it easier to identify trends, patterns, and relationships. By creating graphs from spreadsheet data, users can effectively communicate insights and findings to a broader audience.