Not exact matches
The red
line on this chart
plots 3 - month
averages of ocean heat content.
To remove short - term noise, they
plotted a 12 month running
average of Global Tropospheric Temperature Anomaly (GTTA, the light grey
line) and the Southern Oscillation Index (SOI, the black
line).
This reading divided by the
average from the reading of the six control wells was
plotted to determine the IC50 value of each complex for each cell
line.
Fun characters with slightly above
average plot lines.
Averages 1 - Mode, Median and Mean
Averages 2 - Which
Average is Best
Averages 3 - Grouped Data (Estimated Mean)
Averages 4 - Mean vs Estimated Mean Bar Charts Binomial Distribution 1 - Investigation and Introduction Binomial Distribution 2 - Solving Problems Binomial Distribution 3 - Expectation and Variance Box
Plots Coding Combining Data Sets Cumulative Frequency Discrete Random Variables Expectation and Variance Frequency Polygons Histograms 1 - Drawing Histograms 2 - Interpreting Interpolation - Estimating the Median Moving
Averages Normal Distribution 1 - Standard Normal Normal Distribution 2 - Non-Standard Normal Distribution 3 - Backwards and Further Problems Normal Distribution 4 - Approximation for Binomial Distribution Pictograms Pie Charts 1 - Drawing Pie Charts 2 - Interpreting Product Moment Correlation Coefficient (PMCC) Poisson Distribution Probability 1 Probability 2 Probability 3 Probability 4 Probability 5 Questionnaires Regression
Lines Sampling Scatter Diagrams Sets 1 - 2 sets Sets 2 - 3 sets Sets 3 - Probability Sets 4 - Conditional Probability Skewness Spearman's Rank Correlation Coefficient Standard Deviation and the Variance Stem and Leaf Diagrams Two Way Tables Probability Distribution Function NOTE: Feel free to browse my shop for more excellent free and premium resources and as always please rate and feedback, thank you.
Another way is through data reporting and visualization by presenting raw data (such as histograms and scatterplots) rather than just
averaged data (such as bar or
line plots).
An interactive lesson on moving
averages and
plotting trend
lines - with a set of 8 smart response questions at the end.
A powerpoint and worksheet to revise seasonal products and
averages, then learn how to calculate 4 - point moving
averages, use them to
plot a trend
line and predict future values.
Bollinger Bands — Uses a simple moving
average and
plots two
lines two standard deviations above and below it to form a range.
Bollinger bands are basically 2
lines that are
plotted 2 standard deviations above and below a moving
average for an X amount of time, where X is whatever you want it to be.
A common strategy among chartists and analysts involves
plotting two moving
average lines of different time intervals and interpreting their relationship to spot trends, forecast price movements and place trades.
Several different kinds of moving
average calculations exist, but all of them are used to
plot a
line against either a price chart or another indicator.
A moving
average plots the
average of those prices over a period of time, smoothing out those variations and giving you a
line that shows the overall direction.
Figure 1: Twenty - year smoothed
plots of tree - ring width (dashed
line) and tree - ring density (thick solid
line),
averaged across a network of mid-northern latitude boreal forest sites and compared with equivalent - area
averages of mean April to September temperature anomalies (thin solid
line).
All this Global Warming if you
plot it on a graph with the vertical y - axis incremented in whole degrees you could free hand a straight
line starting from the end of the Little Ice Age all the way to the current day and see there has been no dramatic global
average temperature change since the turn of the 19th century.
The current value of the long term trend
line will vary slowly, but the 12 months running
average and the red circle around the temp in the last month will retain the newsworthiness of the
plot.
One can even see the comb effect where there are a number of absorbing
lines close together (look below 8 microns) and the equivalent radiation temperature varies rapidly with wavelength between surface and tropopause temperature giving a very jagged
plot until the
lines get so close together that the interferometer can not resolve them and one gets a very noisy
average.
Panel (a) shows the CR flux (red
line) from combined Moscow and Climax neutron monitor data, and the globally
averaged ISCCP IR low (> 680 mb / < 3.2 km) cloud anomaly
plotted at a monthly resolution from June 1983 to December 1994, (b) shows the local correlation coefficient (r - values) achieved between the cloud and CR flux data for 12 - month (boxcar) smoothed values.
In the chart below (Figure 1), I have
plotted the entire 118 year record, including the overall
average (solid red
line) and the 95 % confidence range about that mean (+ / - two times the detrended standard deviation; dotted red
lines).
Figure 2: Eight records of local temperature variability on multi-centennial scales throughout the course of the Holocene, and an
average of these (thick dark
line) over the past 12,000 years,
plotted with respect to the mid 20th century
average temperature.
If you download the World Radiation Center Total Solar Irradiance Data into an Excel spreadsheet and
plot it with a trend
line (I did - I can email the data and graph to anyone who wishes it), you will notice the there is on
average, a decrease over the 30 year period, that equates to about 0.5 % per millenia.
Twenty - year smoothed
plots of
averaged ring - width (dashed) and tree - ring density (thick
line),
averaged across all sites, and shown as standardized anomalies from a common base (1881 — 1940), and compared with equivalent - area
averages of mean April — September temperature anomalies (thin solid
line).
The first
plot shows the 5 yr
average temperature for the lower 48: — red
line is for stations with CRN = 1 and CRN = 2 (CRN12, the good stations).