Upload
hayeck
View
22
Download
1
Embed Size (px)
Citation preview
Introduction to using Beamer for PresentationsYou can add a subtitle
Ulrike Genschel
Department of Statistics, Iowa State University
January 24, 2014
U. Genschel (Dep. of Statistics, ISU) Intro Beamer January 24, 2014 1 / 1
Sampling Distributions and the Central Limit Theorem
Describing the sampling distribution of the sample mean x̄ :
mean of the sampling distribution (µx̄)
spread of the sampling distribution (σx̄)
shape of the sampling distribution
A small formula
x̄ approximately N(µ,
σ√n
)
U. Genschel (Dep. of Statistics, ISU) Intro Beamer January 24, 2014 2 / 1
The previous slide somewhat fancier...Sampling Distribution of the sample mean
Describing the sampling distribution of the sample mean x̄ :
mean of the sampling distribution (µx̄)
spread of the sampling distribution (σx̄)
shape of the sampling distribution
A small formula
x̄ approximately N(µ,
σ√n
)
U. Genschel (Dep. of Statistics, ISU) Intro Beamer January 24, 2014 3 / 1
The previous slide somewhat fancier...Sampling Distribution of the sample mean
Describing the sampling distribution of the sample mean x̄ :
mean of the sampling distribution (µx̄)
spread of the sampling distribution (σx̄)
shape of the sampling distribution
A small formula
x̄ approximately N(µ,
σ√n
)
U. Genschel (Dep. of Statistics, ISU) Intro Beamer January 24, 2014 3 / 1
The previous slide somewhat fancier...Sampling Distribution of the sample mean
Describing the sampling distribution of the sample mean x̄ :
mean of the sampling distribution (µx̄)
spread of the sampling distribution (σx̄)
shape of the sampling distribution
A small formula
x̄ approximately N(µ,
σ√n
)
U. Genschel (Dep. of Statistics, ISU) Intro Beamer January 24, 2014 3 / 1
The previous slide somewhat fancier...Sampling Distribution of the sample mean
Describing the sampling distribution of the sample mean x̄ :
mean of the sampling distribution (µx̄)
spread of the sampling distribution (σx̄)
shape of the sampling distribution
A small formula
x̄ approximately N(µ,
σ√n
)
U. Genschel (Dep. of Statistics, ISU) Intro Beamer January 24, 2014 3 / 1
The previous slide somewhat fancier...Sampling Distribution of the sample mean
Describing the sampling distribution of the sample mean x̄ :
mean of the sampling distribution (µx̄)
spread of the sampling distribution (σx̄)
shape of the sampling distribution
A small formula
x̄ approximately N(µ,
σ√n
)
U. Genschel (Dep. of Statistics, ISU) Intro Beamer January 24, 2014 3 / 1
The previous slide somewhat fancier...Sampling Distribution of the sample mean
Describing the sampling distribution of the sample mean x̄ :
mean of the sampling distribution (µx̄)
spread of the sampling distribution (σx̄)
shape of the sampling distribution
A small formula
x̄ approximately N(µ,
σ√n
)
U. Genschel (Dep. of Statistics, ISU) Intro Beamer January 24, 2014 3 / 1
The previous slide somewhat fancier...Sampling Distribution of the sample mean
Describing the sampling distribution of the sample mean x̄ :
mean of the sampling distribution (µx̄)
spread of the sampling distribution (σx̄)
shape of the sampling distribution
a small formula
x̄ approximately N(µ,
σ√n
)
U. Genschel (Dep. of Statistics, ISU) Intro Beamer January 24, 2014 4 / 1
The previous slide somewhat fancier...Sampling Distribution of the sample mean
Describing the sampling distribution of the sample mean x̄ :
mean of the sampling distribution (µx̄)
spread of the sampling distribution (σx̄)
shape of the sampling distribution
a small formula
x̄ approximately N(µ,
σ√n
)
U. Genschel (Dep. of Statistics, ISU) Intro Beamer January 24, 2014 4 / 1
The previous slide somewhat fancier...Sampling Distribution of the sample mean
Describing the sampling distribution of the sample mean x̄ :
mean of the sampling distribution (µx̄)
spread of the sampling distribution (σx̄)
shape of the sampling distribution
a small formula
x̄ approximately N(µ,
σ√n
)
U. Genschel (Dep. of Statistics, ISU) Intro Beamer January 24, 2014 4 / 1
Uncovering text
To uncover text you can use the command
\setbeamercovered{transparent}
U. Genschel (Dep. of Statistics, ISU) Intro Beamer January 24, 2014 5 / 1
Theorems and such
Definition
A triangle that has a right angle is called a right triangle.
Theorem
In a right triangle, the square of hypotenuse equals the sum of squares oftwo other sides.
Proof.
We leave the proof as an exercise to our astute reader. We also suggestthat the reader generalize the proof to non-Euclidean geometries.
U. Genschel (Dep. of Statistics, ISU) Intro Beamer January 24, 2014 6 / 1
Theorems and such
Definition
A triangle that has a right angle is called a right triangle.
Theorem
In a right triangle, the square of hypotenuse equals the sum of squares oftwo other sides.
Proof.
We leave the proof as an exercise to our astute reader. We also suggestthat the reader generalize the proof to non-Euclidean geometries.
U. Genschel (Dep. of Statistics, ISU) Intro Beamer January 24, 2014 6 / 1
Theorems and such
Definition
A triangle that has a right angle is called a right triangle.
Theorem
In a right triangle, the square of hypotenuse equals the sum of squares oftwo other sides.
Proof.
We leave the proof as an exercise to our astute reader. We also suggestthat the reader generalize the proof to non-Euclidean geometries.
U. Genschel (Dep. of Statistics, ISU) Intro Beamer January 24, 2014 6 / 1
Theorems and such
Definition
A triangle that has a right angle is called a right triangle.
Theorem
In a right triangle, the square of hypotenuse equals the sum of squares oftwo other sides.
Proof.
We leave the proof as an exercise to our astute reader. We also suggestthat the reader generalize the proof to non-Euclidean geometries.
U. Genschel (Dep. of Statistics, ISU) Intro Beamer January 24, 2014 6 / 1
Adding Boxes & using enumerated
Describing the sampling distribution of the sample mean x̄ :
1 mean of the sampling distribution (µx̄)
2 spread of the sampling distribution (σx̄)
3 shape of the sampling distribution
Central Limit Theorem (CLT)
If we draw a simple random sample of size n from any population withmean µ and standard deviation σ and n is sufficiently large, then thesampling distribution of the sample mean x̄ is approximately normal:
x̄ approximately N(µ,
σ√n
)
U. Genschel (Dep. of Statistics, ISU) Intro Beamer January 24, 2014 7 / 1
Adding Boxes & using enumerated
Describing the sampling distribution of the sample mean x̄ :
1 mean of the sampling distribution (µx̄)
2 spread of the sampling distribution (σx̄)
3 shape of the sampling distribution
Central Limit Theorem (CLT)
If we draw a simple random sample of size n from any population withmean µ and standard deviation σ and n is sufficiently large, then thesampling distribution of the sample mean x̄ is approximately normal:
x̄ approximately N(µ,
σ√n
)
U. Genschel (Dep. of Statistics, ISU) Intro Beamer January 24, 2014 7 / 1
Adding Boxes & using enumerated
Describing the sampling distribution of the sample mean x̄ :
1 mean of the sampling distribution (µx̄)
2 spread of the sampling distribution (σx̄)
3 shape of the sampling distribution
Central Limit Theorem (CLT)
If we draw a simple random sample of size n from any population withmean µ and standard deviation σ and n is sufficiently large, then thesampling distribution of the sample mean x̄ is approximately normal:
x̄ approximately N(µ,
σ√n
)
U. Genschel (Dep. of Statistics, ISU) Intro Beamer January 24, 2014 7 / 1
Adding Boxes & using enumerated
Describing the sampling distribution of the sample mean x̄ :
1 mean of the sampling distribution (µx̄)
2 spread of the sampling distribution (σx̄)
3 shape of the sampling distribution
Central Limit Theorem (CLT)
If we draw a simple random sample of size n from any population withmean µ and standard deviation σ and n is sufficiently large, then thesampling distribution of the sample mean x̄ is approximately normal:
x̄ approximately N(µ,
σ√n
)
U. Genschel (Dep. of Statistics, ISU) Intro Beamer January 24, 2014 7 / 1
Adding Boxes & using enumerated
Describing the sampling distribution of the sample mean x̄ :
1 mean of the sampling distribution (µx̄)
2 spread of the sampling distribution (σx̄)
3 shape of the sampling distribution
Central Limit Theorem (CLT)
If we draw a simple random sample of size n from any population withmean µ and standard deviation σ and n is sufficiently large, then thesampling distribution of the sample mean x̄ is approximately normal:
x̄ approximately N(µ,
σ√n
)
U. Genschel (Dep. of Statistics, ISU) Intro Beamer January 24, 2014 7 / 1
Adding Boxes & using enumerated
Describing the sampling distribution of the sample mean x̄ :
1 mean of the sampling distribution (µx̄)
2 spread of the sampling distribution (σx̄)
3 shape of the sampling distribution
Central Limit Theorem (CLT)
If we draw a simple random sample of size n from any population withmean µ and standard deviation σ and n is sufficiently large, then thesampling distribution of the sample mean x̄ is approximately normal:
x̄ approximately N(µ,
σ√n
)
U. Genschel (Dep. of Statistics, ISU) Intro Beamer January 24, 2014 7 / 1
Adding Boxes & using enumerated
Describing the sampling distribution of the sample mean x̄ :
1 mean of the sampling distribution (µx̄)
2 spread of the sampling distribution (σx̄)
3 shape of the sampling distribution
Central Limit Theorem (CLT)
If we draw a simple random sample of size n from any population withmean µ and standard deviation σ and n is sufficiently large, then thesampling distribution of the sample mean x̄ is approximately normal:
x̄ approximately N(µ,
σ√n
)
U. Genschel (Dep. of Statistics, ISU) Intro Beamer January 24, 2014 7 / 1
Adding Boxes & using enumerated
Describing the sampling distribution of the sample mean x̄ :
1 mean of the sampling distribution (µx̄)
2 spread of the sampling distribution (σx̄)
3 shape of the sampling distribution
Central Limit Theorem (CLT)
If we draw a simple random sample of size n from any population withmean µ and standard deviation σ and n is sufficiently large, then thesampling distribution of the sample mean x̄ is approximately normal:
x̄ approximately N(µ,
σ√n
)
U. Genschel (Dep. of Statistics, ISU) Intro Beamer January 24, 2014 7 / 1
Changing Itemization Markers
Markers can be changed using the command
\setbeamertemplate{items}[]
\setbeamertemplate{items}[circle]
\setbeamertemplate{items}[ball]
\setbeamertemplate{items}[rectangle]
\setbeamertemplate{items}[triangle]
U. Genschel (Dep. of Statistics, ISU) Intro Beamer January 24, 2014 8 / 1
Changing Itemization Markers
Markers can be changed using the command
\setbeamertemplate{items}[]
\setbeamertemplate{items}[circle]
\setbeamertemplate{items}[ball]
\setbeamertemplate{items}[rectangle]
\setbeamertemplate{items}[triangle]
U. Genschel (Dep. of Statistics, ISU) Intro Beamer January 24, 2014 8 / 1
Changing Itemization Markers
Markers can be changed using the command
\setbeamertemplate{items}[]
\setbeamertemplate{items}[circle]
\setbeamertemplate{items}[ball]
\setbeamertemplate{items}[rectangle]
\setbeamertemplate{items}[triangle]
U. Genschel (Dep. of Statistics, ISU) Intro Beamer January 24, 2014 8 / 1
Changing Itemization Markers
Markers can be changed using the command
\setbeamertemplate{items}[]
\setbeamertemplate{items}[circle]
\setbeamertemplate{items}[ball]
\setbeamertemplate{items}[rectangle]
\setbeamertemplate{items}[triangle]
U. Genschel (Dep. of Statistics, ISU) Intro Beamer January 24, 2014 8 / 1
Including graphs/pictures
The graphics package supports the most common graphic formats .pdf,.jpg, .jpeg, and .png. Other formats must be converted to a supportedformat in an external editor.
rule.pdf
Figure : This is my figure 1.
U. Genschel (Dep. of Statistics, ISU) Intro Beamer January 24, 2014 9 / 1
Splitting a slide into columns
The line you are reading goes all the way across the slide. From the leftmargin to the right margin. Now we are going the split the slide into twocolumns.
Here is the first column. We put anitemized list in it.
This is an item
This is another item
Yet another item
Here is the secondcolumn. We will put apicture in it.
rule.pdf
Figure : Figure 2
The line you are reading goes all the way across the slide. From the leftmargin to the right margin.
U. Genschel (Dep. of Statistics, ISU) Intro Beamer January 24, 2014 10 / 1
Splitting a slide into columns
The line you are reading goes all the way across the slide. From the leftmargin to the right margin. Now we are going the split the slide into twocolumns.
Here is the first column. We put anitemized list in it.
This is an item
This is another item
Yet another item
Here is the secondcolumn. We will put apicture in it.
rule.pdf
The line you are reading goes all the way across the slide. From the leftmargin to the right margin.
U. Genschel (Dep. of Statistics, ISU) Intro Beamer January 24, 2014 11 / 1
The default font size
Beamer’s default font size is 11 points. It is possible to set the defaultfont size to any of 8, 9, 10, 11, 12, 14, 17, 20 in the
\documentclass
For instance, to set the default font to 14 points, do:
\documentclass[14pt]{beamer}
U. Genschel (Dep. of Statistics, ISU) Intro Beamer January 24, 2014 12 / 1
Changing font sizes throughout the presentation
mean of the sampling distribution
the mean of the sampling distribution of the sample mean is equal tothe population mean
µx̄ = µ
spread of the sampling distribution
the spread of the sampling distribution of the sample mean is equal tothe population standard deviation divided by square root of the samplesize
σx̄ = σ√n
U. Genschel (Dep. of Statistics, ISU) Intro Beamer January 24, 2014 13 / 1
Changing font sizes throughout the presentation
mean of the sampling distributionmean of the sampling distributionmean of the sampling distribution
mean of the sampling distributionmean of the sampling distribution
mean of the sampling distributionmean of the sampling distribution
U. Genschel (Dep. of Statistics, ISU) Intro Beamer January 24, 2014 14 / 1
Changing colors
We can change
foreground color (fg)
\setbeamercolor{normal text}{fg=purple}
background color (bg)
\setbeamercolor{normal text}{bg=blue!12}
\setbeamertemplate{background canvas}[vertical shading]
[bottom=red!20,top=yellow!30]
overall color theme of the presentation
\usecolortheme[named=Red]{structure}
Note, many variations of colors are possible — pick whatever you like
U. Genschel (Dep. of Statistics, ISU) Intro Beamer January 24, 2014 15 / 1
Including Page numbers manually
To include page numbers manually (for plain beamer themes e.g. defaultor boxes) use following commands
\usepackage{fancyhdr,lastpage}
\pagestyle{fancy}\fancyhf{}\rfoot{\vspace{-0.5cm} Page
{\thepage} of \pageref{LastPage}}
Need to download following style files fancyhdr.sty and lastpage.sty
U. Genschel (Dep. of Statistics, ISU) Intro Beamer January 24, 2014 16 / 1