movies: General information about the movies
In paulnorthrop/stat1004: stat1004: Introduction to Probability and Statistics at UCL
Description
Details
Value
Examples
References
See Also
Description
These movies are animations used to illustrate key ideas in STAT0002.
They are produced using the package rpanel.package.
You need to install rpanel once, using RStudio's Install button
in the Packages menu or install.packages("rpanel") on the command
line).
Prior to creating a movie the rpanel package must be loaded,
using 'library(rpanel)', in order that these functions work.
If rpanel is not loaded then an error message
similar to Error in shuttle_movie() : could not find function
"rp.control" will be produced.
For the one of the movies the tkrplot package is also required.
See Examples below.
Details
(Some of these movies, and other movies are also available in a more
user-friendly form, via the smovie package.
If you have smovie installed (install.packages("smovie"))
then you can access these using library(smovie) and then
movies().
See movies for more details.)
When one of these functions is called R opens up a small
parameter window containing clickable buttons that can be
used to change parameters underlying the plot. For the effects of
these buttons see the documentation of the individual functions below.
The parameter window does not close automatically after the movie:
the user needs to close it manually.
Some movies create objects in the global environment, that is, objects
that will be listed when ls() is used. rm can be used to remove
these objects if desired. For example rm(name) can be used to remove
object name.
Value
Nothing is returned, only the animation is produced.
Examples
See the examples given for the individual movies listed below.
References
Bowman, A., Crawford, E., Alexander, G. and Bowman, R. W.
(2007). rpanel: Simple Interactive Controls for R Functions Using the
tcltk Package. Journal of Statistical Software, 17(9),
1-18.
http://www.jstatsoft.org/v17/i09/.
See Also
shuttle_movie: illustrates uncertainty in the
linear logistic regression curves fitted to the real space shuttle data.
scatterplot_movie: straightening scatter plots
using variable transformation (US 2000 Presidential Election).
world_bank_movie: explores graphically relationships
between four annual World Bank Development Indicators and how this changes
over time.
ox_births_movie: shows how the shape of a histogram
of simulated data tends to become smoother as the sample size increases.
binomial_pmf_movie: shows how the probability mass
function (p.m.f.) of a binomial random variable depends on its two
parameters.
poisson_process_movie: illustrates the link between
the Poisson process and the Poisson distribution for the number of events
that occur during a time interval of fixed length.
poisson_process_check: uses the plots in
poisson_process_movie to perform informal graphical checks
of whether the arrival times of a sequence of events is consistent
with arising from a Poisson process.
normal_pdf_movie: shows the effect of the
mean and variance parameters of a normal distribution on its p.d.f..
normal_areas_movie: shows how the probability that
a standard normal random variable lies within plus or minus a multiple of
its standard deviation varies with the value of the multiple.
qq_plot_movie: shows how a (normal) QQ plot is
constructed, using a small example dataset.
normal_sampling_distns_movie: shows how the
sampling distributions of the sample mean and sample variance based
on a random sample from a normal distribution depend on the size
n of the sample.
clt_normal_movie: illustrates the ideas of a
sampling distribution of a random variable and the central limit
theorem (CLT), using normally distributed data.
clt_exponential_movie: illustrates the ideas of a
sampling distribution of a random variable and the central limit
theorem (CLT), using exponentially distributed data..
mean_vs_median_normal_movie: compares the
sampling distributions of the sample mean and sample median based
on a random sample of size n from a standard normal distribution.
mean_vs_median_t_movie: compares the
sampling distributions of the sample mean and sample median based
on a random sample of size n from a Student's t distribution.
two_by_two_movie: studies the distribution
of the Pearson chi-squared test statistic used to test for lack of
association in a 2 by 2 contingency table.
lin_reg_movie: visualizes the fitting of a
regression line using least squares.
lev_inf_movie: examine the influence of a
single outlying observation on a least squares regression line.
corr_sim_movie: illustrates the sampling
distribution of the (Pearson product moment) sample correlation
coefficient.
paulnorthrop/stat1004 documentation built on Nov. 17, 2019, 3:49 a.m.
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Description Details Value Examples References See Also
Description
These movies are animations used to illustrate key ideas in STAT0002.
They are produced using the package rpanel.package.
You need to install rpanel once, using RStudio's Install button
in the Packages menu or install.packages("rpanel") on the command
line).
Prior to creating a movie the rpanel package must be loaded,
using 'library(rpanel)', in order that these functions work.
If rpanel is not loaded then an error message
similar to Error in shuttle_movie() : could not find function
"rp.control" will be produced.
For the one of the movies the tkrplot package is also required.
See Examples below.
Details
(Some of these movies, and other movies are also available in a more
user-friendly form, via the smovie package.
If you have smovie installed (install.packages("smovie"))
then you can access these using library(smovie) and then
movies().
See movies for more details.)
When one of these functions is called R opens up a small parameter window containing clickable buttons that can be used to change parameters underlying the plot. For the effects of these buttons see the documentation of the individual functions below.
The parameter window does not close automatically after the movie: the user needs to close it manually.
Some movies create objects in the global environment, that is, objects
that will be listed when ls() is used. rm can be used to remove
these objects if desired. For example rm(name) can be used to remove
object name.
Value
Nothing is returned, only the animation is produced.
Examples
See the examples given for the individual movies listed below.
References
Bowman, A., Crawford, E., Alexander, G. and Bowman, R. W. (2007). rpanel: Simple Interactive Controls for R Functions Using the tcltk Package. Journal of Statistical Software, 17(9), 1-18. http://www.jstatsoft.org/v17/i09/.
See Also
shuttle_movie: illustrates uncertainty in the
linear logistic regression curves fitted to the real space shuttle data.
scatterplot_movie: straightening scatter plots
using variable transformation (US 2000 Presidential Election).
world_bank_movie: explores graphically relationships
between four annual World Bank Development Indicators and how this changes
over time.
ox_births_movie: shows how the shape of a histogram
of simulated data tends to become smoother as the sample size increases.
binomial_pmf_movie: shows how the probability mass
function (p.m.f.) of a binomial random variable depends on its two
parameters.
poisson_process_movie: illustrates the link between
the Poisson process and the Poisson distribution for the number of events
that occur during a time interval of fixed length.
poisson_process_check: uses the plots in
poisson_process_movie to perform informal graphical checks
of whether the arrival times of a sequence of events is consistent
with arising from a Poisson process.
normal_pdf_movie: shows the effect of the
mean and variance parameters of a normal distribution on its p.d.f..
normal_areas_movie: shows how the probability that
a standard normal random variable lies within plus or minus a multiple of
its standard deviation varies with the value of the multiple.
qq_plot_movie: shows how a (normal) QQ plot is
constructed, using a small example dataset.
normal_sampling_distns_movie: shows how the
sampling distributions of the sample mean and sample variance based
on a random sample from a normal distribution depend on the size
n of the sample.
clt_normal_movie: illustrates the ideas of a
sampling distribution of a random variable and the central limit
theorem (CLT), using normally distributed data.
clt_exponential_movie: illustrates the ideas of a
sampling distribution of a random variable and the central limit
theorem (CLT), using exponentially distributed data..
mean_vs_median_normal_movie: compares the
sampling distributions of the sample mean and sample median based
on a random sample of size n from a standard normal distribution.
mean_vs_median_t_movie: compares the
sampling distributions of the sample mean and sample median based
on a random sample of size n from a Student's t distribution.
two_by_two_movie: studies the distribution
of the Pearson chi-squared test statistic used to test for lack of
association in a 2 by 2 contingency table.
lin_reg_movie: visualizes the fitting of a
regression line using least squares.
lev_inf_movie: examine the influence of a
single outlying observation on a least squares regression line.
corr_sim_movie: illustrates the sampling
distribution of the (Pearson product moment) sample correlation
coefficient.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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