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diff --git a/10-MultipleRegression-FactorialDesigns.html b/10-MultipleRegression-FactorialDesigns.html
@@ -700,15 +700,15 @@ <h2><span class="header-section-number">4.1</span> Verwijderen van
 
 Linear Hypotheses:
                       Estimate Std. Error t value Pr(&gt;|t|)    
-poison: II - I == 0    0.04686    0.01744   2.688  0.07352 .  
+poison: II - I == 0    0.04686    0.01744   2.688  0.07355 .  
 poison: III - I == 0   0.19964    0.01744  11.451  &lt; 0.001 ***
 poison: III - II == 0  0.15278    0.01744   8.763  &lt; 0.001 ***
 treat: B - A == 0     -0.16574    0.02013  -8.233  &lt; 0.001 ***
-treat: C - A == 0     -0.05721    0.02013  -2.842  0.05085 .  
+treat: C - A == 0     -0.05721    0.02013  -2.842  0.05088 .  
 treat: D - A == 0     -0.13583    0.02013  -6.747  &lt; 0.001 ***
 treat: C - B == 0      0.10853    0.02013   5.391  &lt; 0.001 ***
-treat: D - B == 0      0.02991    0.02013   1.485  0.61546    
-treat: D - C == 0     -0.07862    0.02013  -3.905  0.00282 ** 
+treat: D - B == 0      0.02991    0.02013   1.485  0.61547    
+treat: D - C == 0     -0.07862    0.02013  -3.905  0.00274 ** 
 ---
 Signif. codes:  0 &#39;***&#39; 0.001 &#39;**&#39; 0.01 &#39;*&#39; 0.05 &#39;.&#39; 0.1 &#39; &#39; 1
 (Adjusted p values reported -- single-step method)</code></pre>
@@ -721,21 +721,21 @@ <h2><span class="header-section-number">4.1</span> Verwijderen van
 
 Fit: lm(formula = 1/time ~ poison + treat, data = rats)
 
-Quantile = 2.8497
+Quantile = 2.8499
 95% family-wise confidence level
 
 
 Linear Hypotheses:
                       Estimate   lwr        upr       
-poison: II - I == 0    0.0468641 -0.0028208  0.0965491
-poison: III - I == 0   0.1996425  0.1499575  0.2493274
-poison: III - II == 0  0.1527784  0.1030934  0.2024633
-treat: B - A == 0     -0.1657402 -0.2231115 -0.1083690
-treat: C - A == 0     -0.0572135 -0.1145848  0.0001577
-treat: D - A == 0     -0.1358338 -0.1932051 -0.0784626
-treat: C - B == 0      0.1085267  0.0511554  0.1658979
-treat: D - B == 0      0.0299064 -0.0274648  0.0872777
-treat: D - C == 0     -0.0786203 -0.1359915 -0.0212490</code></pre>
+poison: II - I == 0    0.0468641 -0.0028243  0.0965526
+poison: III - I == 0   0.1996425  0.1499540  0.2493310
+poison: III - II == 0  0.1527784  0.1030899  0.2024668
+treat: B - A == 0     -0.1657402 -0.2231155 -0.1083649
+treat: C - A == 0     -0.0572135 -0.1145888  0.0001618
+treat: D - A == 0     -0.1358338 -0.1932091 -0.0784585
+treat: C - B == 0      0.1085267  0.0511514  0.1659020
+treat: D - B == 0      0.0299064 -0.0274689  0.0872817
+treat: D - C == 0     -0.0786203 -0.1359956 -0.0212450</code></pre>
 <div class="sourceCode" id="cb17"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb17-1"><a href="#cb17-1" aria-hidden="true" tabindex="-1"></a><span class="fu">plot</span>(comparisons,<span class="at">yaxt=</span><span class="st">&quot;none&quot;</span>)</span>
 <span id="cb17-2"><a href="#cb17-2" aria-hidden="true" tabindex="-1"></a>contrastNames <span class="ot">&lt;-</span> <span class="fu">c</span>(<span class="st">&quot;II-I&quot;</span>,<span class="st">&quot;III-I&quot;</span>,<span class="st">&quot;III-II&quot;</span>,<span class="st">&quot;B-A&quot;</span>,<span class="st">&quot;C-A&quot;</span>,<span class="st">&quot;D-A&quot;</span>,<span class="st">&quot;C-B&quot;</span>,<span class="st">&quot;D-B&quot;</span>,<span class="st">&quot;D-C&quot;</span>)</span>
 <span id="cb17-3"><a href="#cb17-3" aria-hidden="true" tabindex="-1"></a><span class="fu">axis</span>(<span class="dv">2</span>,<span class="at">at=</span><span class="fu">c</span>(<span class="fu">length</span>(contrastNames)<span class="sc">:</span><span class="dv">1</span>), <span class="at">labels=</span>contrastNames,<span class="at">las=</span><span class="dv">2</span>)</span></code></pre></div>

diff --git a/10-MultipleRegression-FactorialDesigns.pdf b/10-MultipleRegression-FactorialDesigns.pdf
diff --git a/10-MultipleRegression-FactorialDesigns_files/figure-html/unnamed-chunk-11-1.png b/10-MultipleRegression-FactorialDesigns_files/figure-html/unnamed-chunk-11-1.png
diff --git a/10-MultipleRegression-FactorialDesigns_files/figure-html/unnamed-chunk-12-1.png b/10-MultipleRegression-FactorialDesigns_files/figure-html/unnamed-chunk-12-1.png
diff --git a/10-MultipleRegression-FactorialDesigns_files/figure-html/unnamed-chunk-2-1.png b/10-MultipleRegression-FactorialDesigns_files/figure-html/unnamed-chunk-2-1.png
diff --git a/10-MultipleRegression-FactorialDesigns_files/figure-html/unnamed-chunk-4-1.png b/10-MultipleRegression-FactorialDesigns_files/figure-html/unnamed-chunk-4-1.png
diff --git a/10-MultipleRegression-FactorialDesigns_files/figure-html/unnamed-chunk-5-1.png b/10-MultipleRegression-FactorialDesigns_files/figure-html/unnamed-chunk-5-1.png
diff --git a/10-MultipleRegression-FactorialDesigns_files/figure-html/unnamed-chunk-9-1.png b/10-MultipleRegression-FactorialDesigns_files/figure-html/unnamed-chunk-9-1.png
diff --git a/10-MultipleRegression.pdf b/10-MultipleRegression.pdf
diff --git a/10-Recap-AlgemeenLineairModel-AdditiefModel.pdf b/10-Recap-AlgemeenLineairModel-AdditiefModel.pdf
diff --git a/10-Recap-AlgemeenLineairModel-OverigeConcepten.html b/10-Recap-AlgemeenLineairModel-OverigeConcepten.html
@@ -905,14 +905,14 @@ <h3><span class="header-section-number">4.1.2</span> Besluitvorming</h3>
 ## 
 ## Fit: lm(formula = BPSysAve ~ Age * Gender, data = bpData, weights = 1/mSd$fitted^2)
 ## 
-## Quantile = 2.3167
+## Quantile = 2.317
 ## 95% family-wise confidence level
 ##  
 ## 
 ## Linear Hypotheses:
 ##                           Estimate lwr     upr    
 ## Age == 0                   0.4400   0.4050  0.4750
-## Age + Age:Gendermale == 0  0.2484   0.2049  0.2919
+## Age + Age:Gendermale == 0  0.2484   0.2048  0.2919
 ## Age:Gendermale == 0       -0.1916  -0.2475 -0.1357</code></pre>
 </div>
 <div id="conclusie" class="section level3" number="4.1.3">

diff --git a/10-Recap-AlgemeenLineairModel-OverigeConcepten.pdf b/10-Recap-AlgemeenLineairModel-OverigeConcepten.pdf
diff --git a/...-AlgemeenLineairModel-OverigeConcepten_files/figure-html/unnamed-chunk-26-1.png b/...-AlgemeenLineairModel-OverigeConcepten_files/figure-html/unnamed-chunk-26-1.png
diff --git a/...-AlgemeenLineairModel-OverigeConcepten_files/figure-html/unnamed-chunk-27-1.png b/...-AlgemeenLineairModel-OverigeConcepten_files/figure-html/unnamed-chunk-27-1.png
diff --git a/...-AlgemeenLineairModel-OverigeConcepten_files/figure-html/unnamed-chunk-30-1.png b/...-AlgemeenLineairModel-OverigeConcepten_files/figure-html/unnamed-chunk-30-1.png
diff --git a/Examenvoorbeeld_oefening_1.html b/Examenvoorbeeld_oefening_1.html
@@ -743,7 +743,7 @@ <h1><span class="header-section-number">3</span> Hypotheses testen</h1>
 ##                            Estimate Std. Error t value Pr(&gt;|t|)    
 ## bacon == 0                 -1.19081    0.13182  -9.034   &lt;0.001 ***
 ## bacon + bacon:sexmale == 0 -0.87572    0.06286 -13.930   &lt;0.001 ***
-## bacon:sexmale == 0          0.31509    0.14603   2.158   0.0734 .  
+## bacon:sexmale == 0          0.31509    0.14603   2.158   0.0736 .  
 ## ---
 ## Signif. codes:  0 &#39;***&#39; 0.001 &#39;**&#39; 0.01 &#39;*&#39; 0.05 &#39;.&#39; 0.1 &#39; &#39; 1
 ## (Adjusted p values reported -- single-step method)</code></pre>
@@ -754,15 +754,15 @@ <h1><span class="header-section-number">3</span> Hypotheses testen</h1>
 ## 
 ## Fit: lm(formula = permeat ~ bacon + length + sex + bacon:sex, data = pigs)
 ## 
-## Quantile = 2.3172
+## Quantile = 2.3178
 ## 95% family-wise confidence level
 ##  
 ## 
 ## Linear Hypotheses:
 ##                            Estimate lwr      upr     
-## bacon == 0                 -1.19081 -1.49627 -0.88535
-## bacon + bacon:sexmale == 0 -0.87572 -1.02139 -0.73005
-## bacon:sexmale == 0          0.31509 -0.02329  0.65347</code></pre>
+## bacon == 0                 -1.19081 -1.49634 -0.88528
+## bacon + bacon:sexmale == 0 -0.87572 -1.02142 -0.73001
+## bacon:sexmale == 0          0.31509 -0.02337  0.65355</code></pre>
 </div>
 <div id="conclusie" class="section level1" number="4">
 <h1><span class="header-section-number">4</span> Conclusie</h1>

diff --git a/Examenvoorbeeld_oefening_1.pdf b/Examenvoorbeeld_oefening_1.pdf
diff --git a/Examenvoorbeeld_oefening_2.html b/Examenvoorbeeld_oefening_2.html
@@ -692,7 +692,7 @@ <h1><span class="header-section-number">3</span> Hypotheses testen</h1>
 ##                                  Estimate Std. Error t value Pr(&gt;|t|)    
 ## tissueV == 0                       7.9680     0.4532  17.580   &lt;0.001 ***
 ## tissueV + locationR:tissueV == 0   5.5038     0.4532  12.143   &lt;0.001 ***
-## locationR:tissueV == 0            -2.4641     0.6410  -3.844   0.0193 *  
+## locationR:tissueV == 0            -2.4641     0.6410  -3.844   0.0195 *  
 ## ---
 ## Signif. codes:  0 &#39;***&#39; 0.001 &#39;**&#39; 0.01 &#39;*&#39; 0.05 &#39;.&#39; 0.1 &#39; &#39; 1
 ## (Adjusted p values reported -- single-step method)</code></pre>
@@ -703,24 +703,24 @@ <h1><span class="header-section-number">3</span> Hypotheses testen</h1>
 ## Fit: lm(formula = intensity %&gt;% log2 ~ location * tissue + patient, 
 ##     data = hart)
 ## 
-## Quantile = 3.0262
+## Quantile = 3.0167
 ## 95% family-wise confidence level
 ##  
 ## 
 ## Linear Hypotheses:
 ##                                  Estimate lwr     upr    
-## tissueV == 0                      7.9680   6.5963  9.3396
-## tissueV + locationR:tissueV == 0  5.5038   4.1322  6.8755
-## locationR:tissueV == 0           -2.4641  -4.4039 -0.5244</code></pre>
+## tissueV == 0                      7.9680   6.6006  9.3353
+## tissueV + locationR:tissueV == 0  5.5038   4.1365  6.8711
+## locationR:tissueV == 0           -2.4641  -4.3978 -0.5304</code></pre>
 <div class="sourceCode" id="cb29"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb29-1"><a href="#cb29-1" aria-hidden="true" tabindex="-1"></a><span class="dv">2</span><span class="sc">^</span><span class="fu">confint</span>(mcp)<span class="sc">$</span>confint</span></code></pre></div>
 <pre><code>##                                Estimate         lwr         upr
-## tissueV                     250.3757829 96.85309171 647.2486482
-## tissueV + locationR:tissueV  45.3753769 17.55259829 117.3002876
-## locationR:tissueV             0.1812291  0.04730366   0.6943223
+## tissueV                     250.3757829 96.81778511 647.4846807
+## tissueV + locationR:tissueV  45.3753769 17.54619970 117.3430636
+## locationR:tissueV             0.1812291  0.04727928   0.6946804
 ## attr(,&quot;conf.level&quot;)
 ## [1] 0.95
 ## attr(,&quot;calpha&quot;)
-## [1] 3.023148</code></pre>
+## [1] 3.024308</code></pre>
 </div>
 <div id="conclusie" class="section level1" number="4">
 <h1><span class="header-section-number">4</span> Conclusie:</h1>
@@ -729,10 +729,10 @@ <h1><span class="header-section-number">4</span> Conclusie:</h1>
 0.001).</p>
 <p>Het geometrisch gemiddelde van de expressie van Myosin3L is een
 factor 250 hoger in het linkerventrikel dan in het linkeratrium (p &lt;
-0.001, 95% BI [96.5, 649.4]).</p>
+0.001, 95% BI [96.8, 647.9]).</p>
 <p>Het geometrisch gemiddelde van de expressie van Myosin3L is een
 factor 45 hoger in het rechterventrikel dan in het rechteratrium (p &lt;
-0.001, 95% BI [17.6, 117.2]).</p>
+0.001, 95% BI [17.5, 117.4]).</p>
 <p>De opregulatie van Myosin3L in ventrikel vs het atrium is gemiddeld
 een factor 6 hoger in de linker- dan in de rechterzijde (p = 0.018, 95%
 BI [1.4, 21.1] ).</p>

diff --git a/Examenvoorbeeld_oefening_2.pdf b/Examenvoorbeeld_oefening_2.pdf
diff --git a/Examenvoorbeeld_oefening_2_opgave.pdf b/Examenvoorbeeld_oefening_2_opgave.pdf
diff --git a/Exp_design_fast_1_sol.html b/Exp_design_fast_1_sol.html
@@ -677,9 +677,9 @@ <h2><span class="header-section-number">4.2</span> Simulation</h2>
 <span id="cb15-4"><a href="#cb15-4" aria-hidden="true" tabindex="-1"></a>alpha <span class="ot">&lt;-</span> <span class="fl">0.05</span> </span>
 <span id="cb15-5"><a href="#cb15-5" aria-hidden="true" tabindex="-1"></a>power <span class="ot">&lt;-</span> <span class="fu">simFast</span>(form, rodents, betas, sd, <span class="at">contrasts =</span> contrast, <span class="at">alpha =</span> alpha, <span class="at">nSim =</span> nSim)</span>
 <span id="cb15-6"><a href="#cb15-6" aria-hidden="true" tabindex="-1"></a>power</span></code></pre></div>
-<pre><code>## [1] 0.2137</code></pre>
+<pre><code>## [1] 0.2239</code></pre>
 <p>We observe that the experiment is severly underpowered. We only have
-a power of 21.4% to pick up the treatment effect.</p>
+a power of 22.4% to pick up the treatment effect.</p>
 </div>
 </div>
 <div id="power-for-a-balanced-design" class="section level1" number="5">
@@ -696,7 +696,7 @@ <h1><span class="header-section-number">5</span> Power for a balanced
 <span id="cb19-2"><a href="#cb19-2" aria-hidden="true" tabindex="-1"></a>predictorData <span class="ot">&lt;-</span> <span class="fu">data.frame</span>(<span class="at">group =</span> <span class="fu">rep</span>(<span class="fu">c</span>(<span class="st">&quot;ctrl&quot;</span>,<span class="st">&quot;treat&quot;</span>),<span class="fu">c</span>(n1,n2)) <span class="sc">%&gt;%</span> as.factor)</span>
 <span id="cb19-3"><a href="#cb19-3" aria-hidden="true" tabindex="-1"></a>powerBalanced <span class="ot">&lt;-</span> <span class="fu">simFast</span>(form, predictorData, betas, sd, <span class="at">contrasts =</span> contrast, <span class="at">alpha =</span> alpha, <span class="at">nSim =</span> nSim)</span>
 <span id="cb19-4"><a href="#cb19-4" aria-hidden="true" tabindex="-1"></a>powerBalanced</span></code></pre></div>
-<pre><code>## [1] 0.2462</code></pre>
+<pre><code>## [1] 0.2596</code></pre>
 <p>We observe that the power is larger for the balanced design. We could
 also have known this from formula of the standard error from the
 two-sample t-test.</p>

diff --git a/Exp_design_fast_1_sol.pdf b/Exp_design_fast_1_sol.pdf
diff --git a/Exp_design_fast_1_sol_files/figure-html/unnamed-chunk-3-1.png b/Exp_design_fast_1_sol_files/figure-html/unnamed-chunk-3-1.png
diff --git a/Exp_design_fast_2_sol.html b/Exp_design_fast_2_sol.html
@@ -606,10 +606,10 @@ <h2><span class="header-section-number">1.3</span> Power for <span
 <span id="cb7-10"><a href="#cb7-10" aria-hidden="true" tabindex="-1"></a></span>
 <span id="cb7-11"><a href="#cb7-11" aria-hidden="true" tabindex="-1"></a>power <span class="ot">&lt;-</span> <span class="fu">simFast</span>(form, Puromycin, betas, sd, <span class="at">contrasts =</span> contrast, <span class="at">alpha =</span> alpha, <span class="at">nSim =</span> nSim)</span>
 <span id="cb7-12"><a href="#cb7-12" aria-hidden="true" tabindex="-1"></a>power</span></code></pre></div>
-<pre><code>[1] 0.4223</code></pre>
+<pre><code>[1] 0.4285</code></pre>
 <p>The power to pick up a slope of <span
 class="math inline">\(\beta_1=10\)</span> for this experiment is only
-42.2%.</p>
+42.9%.</p>
 </div>
 <div
 id="calculate-the-number-of-repeats-needed-per-concentration-to-obtain-a-power-of-90-to-pick-up-an-effect-of-beta_110."
@@ -672,7 +672,7 @@ <h1><span class="header-section-number">2</span> Optimal design with 12
 </div>
 <div class="sourceCode" id="cb11"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb11-1"><a href="#cb11-1" aria-hidden="true" tabindex="-1"></a>powerOpt <span class="ot">&lt;-</span> <span class="fu">simFast</span>(form, simData, betas, sd, <span class="at">contrasts =</span> contrast, <span class="at">alpha =</span> alpha, <span class="at">nSim =</span> nSim)</span>
 <span id="cb11-2"><a href="#cb11-2" aria-hidden="true" tabindex="-1"></a>powerOpt</span></code></pre></div>
-<pre><code>[1] 0.6081</code></pre>
+<pre><code>[1] 0.6047</code></pre>
 <p>Note that the power for a design where we repeat each concentration 1
 time and the minimum and maximum concentration 4 times is considerably
 higher than that for the designs where we repeat all data points.</p>

diff --git a/Exp_design_fast_2_sol.pdf b/Exp_design_fast_2_sol.pdf
diff --git a/Exp_design_fast_2_sol_files/figure-html/unnamed-chunk-7-1.png b/Exp_design_fast_2_sol_files/figure-html/unnamed-chunk-7-1.png
diff --git a/Exp_design_fast_2_sol_files/figure-html/unnamed-chunk-9-1.png b/Exp_design_fast_2_sol_files/figure-html/unnamed-chunk-9-1.png
diff --git a/Exp_design_fast_3_sol.html b/Exp_design_fast_3_sol.html
@@ -683,9 +683,9 @@ <h2><span class="header-section-number">2.1</span> Import KPNA2 data in
 ##                            Estimate Std. Error t value Pr(&gt;|t|)    
 ## grade3 == 0                  1.6675     0.1827   9.127  &lt; 0.001 ***
 ## grade3 + grade3:node1 == 0   0.8928     0.1827   4.886  &lt; 0.001 ***
-## node1 == 0                   0.6577     0.1827   3.600  0.00712 ** 
-## node1 + grade3:node1 == 0   -0.1170     0.1827  -0.640  0.89823    
-## grade3:node1 == 0           -0.7748     0.2584  -2.998  0.02653 *  
+## node1 == 0                   0.6577     0.1827   3.600  0.00728 ** 
+## node1 + grade3:node1 == 0   -0.1170     0.1827  -0.640  0.89822    
+## grade3:node1 == 0           -0.7748     0.2584  -2.998  0.02662 *  
 ## ---
 ## Signif. codes:  0 &#39;***&#39; 0.001 &#39;**&#39; 0.01 &#39;*&#39; 0.05 &#39;.&#39; 0.1 &#39; &#39; 1
 ## (Adjusted p values reported -- single-step method)</code></pre>
@@ -744,7 +744,7 @@ <h2><span class="header-section-number">3.2</span> power of current
 <span id="cb32-13"><a href="#cb32-13" aria-hidden="true" tabindex="-1"></a>power1 <span class="ot">&lt;-</span> <span class="fu">simFastMultipleContrasts</span>(form, kpna2, betas, sd, contrasts, <span class="at">nSim =</span> nSim)</span>
 <span id="cb32-14"><a href="#cb32-14" aria-hidden="true" tabindex="-1"></a>power1</span></code></pre></div>
 <pre><code>##     graden0     graden1      nodeg1      nodeg3 interaction 
-##     1.00000     0.97115     0.77105     0.02580     0.57105</code></pre>
+##     1.00000     0.97210     0.77340     0.02430     0.57225</code></pre>
 <p>We observe large powers for all contrasts, except for contrast
 nodeg3, which has a small effect size.</p>
 </div>
@@ -780,15 +780,15 @@ <h2><span class="header-section-number">3.3</span> Power for increasing
 <span id="cb34-26"><a href="#cb34-26" aria-hidden="true" tabindex="-1"></a>}</span>
 <span id="cb34-27"><a href="#cb34-27" aria-hidden="true" tabindex="-1"></a>powers</span></code></pre></div>
 <pre><code>##        n graden0 graden1  nodeg1  nodeg3 interaction
-##  [1,]  2 0.70525 0.21170 0.11090 0.01155     0.07710
-##  [2,]  3 0.99170 0.56765 0.29185 0.01600     0.19135
-##  [3,]  4 0.99995 0.80185 0.47860 0.01945     0.31810
-##  [4,]  5 1.00000 0.92250 0.64605 0.02170     0.45465
-##  [5,]  6 1.00000 0.96890 0.76020 0.02395     0.56840
-##  [6,]  7 1.00000 0.98930 0.85155 0.02610     0.66720
-##  [7,]  8 1.00000 0.99650 0.90705 0.03195     0.74735
-##  [8,]  9 1.00000 0.99895 0.94380 0.03340     0.81375
-##  [9,] 10 1.00000 0.99940 0.96920 0.03760     0.86985</code></pre>
+##  [1,]  2 0.70425 0.21590 0.10945 0.01315     0.07565
+##  [2,]  3 0.99330 0.56650 0.29390 0.01475     0.19335
+##  [3,]  4 0.99985 0.80505 0.48135 0.01875     0.31890
+##  [4,]  5 1.00000 0.91870 0.63915 0.02080     0.44875
+##  [5,]  6 1.00000 0.97270 0.76385 0.02415     0.57265
+##  [6,]  7 1.00000 0.98935 0.85140 0.02930     0.67180
+##  [7,]  8 1.00000 0.99680 0.90725 0.03055     0.75520
+##  [8,]  9 1.00000 0.99900 0.94380 0.03385     0.81975
+##  [9,] 10 1.00000 0.99960 0.96910 0.03955     0.86520</code></pre>
 <div class="sourceCode" id="cb36"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb36-1"><a href="#cb36-1" aria-hidden="true" tabindex="-1"></a>powers <span class="sc">%&gt;%</span> </span>
 <span id="cb36-2"><a href="#cb36-2" aria-hidden="true" tabindex="-1"></a>  as.data.frame <span class="sc">%&gt;%</span> </span>
 <span id="cb36-3"><a href="#cb36-3" aria-hidden="true" tabindex="-1"></a>  <span class="fu">gather</span>(contrast, power, <span class="sc">-</span>n) <span class="sc">%&gt;%</span> </span>
@@ -818,7 +818,7 @@ <h2><span class="header-section-number">3.4</span> Power when FC for
 <span id="cb37-14"><a href="#cb37-14" aria-hidden="true" tabindex="-1"></a>power3 <span class="ot">&lt;-</span> <span class="fu">simFastMultipleContrasts</span>(form, kpna2, betas2, sd, contrasts,<span class="at">nSim =</span> nSim)</span>
 <span id="cb37-15"><a href="#cb37-15" aria-hidden="true" tabindex="-1"></a>power3</span></code></pre></div>
 <pre><code>##     graden0     graden1      nodeg1      nodeg3 interaction 
-##     0.63860     0.05100     0.76620     0.02570     0.56395</code></pre>
+##     0.63630     0.05205     0.76120     0.02380     0.56895</code></pre>
 <p>It is clear that only the power of the contrasts containing <span
 class="math inline">\(\beta_g\)</span> change when the effect size of
 <span class="math inline">\(\beta_g\)</span> changes.</p>

diff --git a/Exp_design_fast_3_sol.pdf b/Exp_design_fast_3_sol.pdf
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diff --git a/Practicum_1_oefening_4.pdf b/Practicum_1_oefening_4.pdf
diff --git a/Practicum_1_oplossing_Two_sample_t_test.pdf b/Practicum_1_oplossing_Two_sample_t_test.pdf
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diff --git a/Practicum_1_oplossing_anova.html b/Practicum_1_oplossing_anova.html
@@ -769,9 +769,9 @@ <h2><span class="header-section-number">3.4</span> Post-hoc analyse</h2>
 ## 
 ## Linear Hypotheses:
 ##                        Estimate Std. Error t value Pr(&gt;|t|)    
-## linseed - casein == 0   -104.83      23.28  -4.504 0.000201 ***
-## soybean - casein == 0    -77.15      22.43  -3.440 0.004220 ** 
-## soybean - linseed == 0    27.68      22.43   1.234 0.441428    
+## linseed - casein == 0   -104.83      23.28  -4.504  &lt; 0.001 ***
+## soybean - casein == 0    -77.15      22.43  -3.440  0.00432 ** 
+## soybean - linseed == 0    27.68      22.43   1.234  0.44141    
 ## ---
 ## Signif. codes:  0 &#39;***&#39; 0.001 &#39;**&#39; 0.01 &#39;*&#39; 0.05 &#39;.&#39; 0.1 &#39; &#39; 1
 ## (Adjusted p values reported -- single-step method)</code></pre>
@@ -805,15 +805,15 @@ <h2><span class="header-section-number">3.4</span> Post-hoc analyse</h2>
 ## 
 ## Fit: lm(formula = weight ~ feed, data = chickwts)
 ## 
-## Quantile = 2.4459
+## Quantile = 2.4472
 ## 95% family-wise confidence level
 ##  
 ## 
 ## Linear Hypotheses:
 ##                        Estimate  lwr       upr      
-## linseed - casein == 0  -104.8333 -161.7640  -47.9026
-## soybean - casein == 0   -77.1548 -132.0146  -22.2950
-## soybean - linseed == 0   27.6786  -27.1812   82.5384</code></pre>
+## linseed - casein == 0  -104.8333 -161.7946  -47.8720
+## soybean - casein == 0   -77.1548 -132.0440  -22.2655
+## soybean - linseed == 0   27.6786  -27.2107   82.5678</code></pre>
 <div class="sourceCode" id="cb18"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb18-1"><a href="#cb18-1" aria-hidden="true" tabindex="-1"></a><span class="fu">plot</span>(mcp)</span></code></pre></div>
 <p><img src="Practicum_1_oplossing_anova_files/figure-html/unnamed-chunk-13-1.png" width="672" /></p>
 </div>

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diff --git a/anova_example.pdf b/anova_example.pdf
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diff --git a/experimentalDesignII_files/figure-html/unnamed-chunk-12-1.png b/experimentalDesignII_files/figure-html/unnamed-chunk-12-1.png
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diff --git a/fishtank_sol.html b/fishtank_sol.html
@@ -668,13 +668,13 @@ <h2><span class="header-section-number">6.4</span> Post-hoc
 <div class="sourceCode" id="cb12"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb12-1"><a href="#cb12-1" aria-hidden="true" tabindex="-1"></a>confDiet <span class="ot">&lt;-</span> <span class="fu">confint</span>(multComp)</span>
 <span id="cb12-2"><a href="#cb12-2" aria-hidden="true" tabindex="-1"></a>confDiet<span class="sc">$</span>confint</span></code></pre></div>
 <pre><code>##       Estimate      lwr      upr
-## 2 - 1 20.33333 12.79575 27.87091
-## 3 - 1 44.00000 36.46242 51.53758
-## 3 - 2 23.66667 16.12909 31.20425
+## 2 - 1 20.33333 12.79917 27.86750
+## 3 - 1 44.00000 36.46584 51.53416
+## 3 - 2 23.66667 16.13250 31.20083
 ## attr(,&quot;conf.level&quot;)
 ## [1] 0.95
 ## attr(,&quot;calpha&quot;)
-## [1] 2.793755</code></pre>
+## [1] 2.792487</code></pre>
 </div>
 <div id="conclusion" class="section level2" number="6.5">
 <h2><span class="header-section-number">6.5</span> Conclusion</h2>

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