diff --git a/03-basics-factors-dataframes.md b/03-basics-factors-dataframes.md
index c6354487..497adee8 100644
--- a/03-basics-factors-dataframes.md
+++ b/03-basics-factors-dataframes.md
@@ -181,7 +181,7 @@ you have the `variants` object, listed as 801 obs. (observations/rows)
 of 29 variables (columns). Double-clicking on the name of the object will open
 a view of the data in a new tab.
 
-<img src="fig/rstudio_dataframeview.png" alt="rstudio data frame view" style="width: 1000px;"/>
+![RStudio data frame view]("fig/rstudio_dataframeview.png")
 
 ## Summarizing, subsetting, and determining the structure of a data frame.
 
@@ -512,7 +512,7 @@ These packages will be installed into "~/work/genomics-r-intro/genomics-r-intro/
 
 # Installing packages --------------------------------------------------------
 - Installing ggplot2 ...                        OK [linked from cache]
-Successfully installed 1 package in 5.2 milliseconds.
+Successfully installed 1 package in 5.5 milliseconds.
 ```
 
 ::::::::::::::::::::::::::::::::::::::::::::::::::
@@ -1263,12 +1263,12 @@ First, in the RStudio menu go to **File**, select **Import Dataset**, and
 choose **From Excel...** (notice there are several other options you can
 explore).
 
-<img src="fig/rstudio_import_menu.png " alt="rstudio import menu" style="width: 600px;"/>
+![RStudio import menu]("fig/rstudio_import_menu.png")
 
 Next, under **File/Url:** click the <KBD>Browse</KBD> button and navigate to the **Ecoli\_metadata.xlsx** file located at `/home/dcuser/dc_sample_data/R`.
 You should now see a preview of the data to be imported:
 
-<img src="fig/rstudio_import_screen.png " alt="rstudio import screen" style="width: 1200px;"/>
+![RStudio import screen]("fig/rstudio_import_screen.png")
 
 Notice that you have the option to change the data type of each variable by
 clicking arrow (drop-down menu) next to each column title. Under **Import
diff --git a/md5sum.txt b/md5sum.txt
index cd7b826c..01939743 100644
--- a/md5sum.txt
+++ b/md5sum.txt
@@ -6,7 +6,7 @@
 "episodes/00-introduction.Rmd" "e1354ed92fb458179c8c00b00ee1cf55" "site/built/00-introduction.md" "2024-04-04"
 "episodes/01-r-basics.Rmd" "2f4b7fd244990f97e0c2fe88bae2618b" "site/built/01-r-basics.md" "2024-04-04"
 "episodes/02-data-prelude.Rmd" "ab2b1fd3cdaae919f9e409f713a0a8ad" "site/built/02-data-prelude.md" "2024-04-04"
-"episodes/03-basics-factors-dataframes.Rmd" "d46879cbe37a7b1f21a9ed50f49ed4d5" "site/built/03-basics-factors-dataframes.md" "2024-04-10"
+"episodes/03-basics-factors-dataframes.Rmd" "78de77380f2b4bfd76622a8fc1e10f99" "site/built/03-basics-factors-dataframes.md" "2024-04-10"
 "episodes/04-bioconductor-vcfr.Rmd" "10eb69b4697d7ecb9695d36c0d974208" "site/built/04-bioconductor-vcfr.md" "2024-04-04"
 "episodes/05-dplyr.Rmd" "f74055bd8677338a213e0a0c6c430119" "site/built/05-dplyr.md" "2024-04-04"
 "episodes/06-data-visualization.Rmd" "0b45534421bad05f040b24c40b6da71b" "site/built/06-data-visualization.md" "2024-04-04"