Update results, conclusions and interactive parts

06-interactive.Rmd

@@ -54,3 +54,8 @@
  <p id="nonFarm"><button type="button">Change to Non-farm Sector</button></p>
 
  <script src="scripts/interactive_bar.js"></script>
+
+<p> 
+The interactive bar graph shows the total number of Work From Home employees change in 2020 by month. 
+Click on the buttons, we can explore that each sector has the lowest rate of Work From Home employees in October.
+</p>

docs/conclusion.html

@@ -125,8 +125,9 @@ <h1><span class="header-section-number">Chapter 7</span> Conclusion</h1>
 <h2><span class="header-section-number">7.1</span> Lessons Learned</h2>
 <p>This study found a number of notable associations between variables, which motivate further research.</p>
 <ul>
-<li><p>Regarding the teleworking population, it has been continuously growing even before COVID happened. The unprecedented pandemic has suddenly increased the WFH population ratio over total employed populations. Among sectors, <code>Construction</code>, <code>Professional</code> and <code>Management, Business and Finance</code> tend to have rooms for increasing number of employees to telecommute on an daily basis.</p></li>
+<li><p>Regarding the teleworking population, it has been continuously growing even before COVID happened. The unprecedented pandemic has suddenly increased the WFH population ratio over total employed populations, which could potentially mean that remote working is more stable than on-site working, given the situation. Among sectors, <code>Construction</code>, <code>Professional</code> and <code>Management, Business and Finance</code> tend to have rooms for increasing number of employees to telecommute on an daily basis.</p></li>
 <li><p>From the graphs of section 5.2 part II, we conclude that there tends to be a positive correlation between Productivity and percentage of employees work from home. The result leads to an opposite direction as our initial thoughts. Three sectors (Manufacturing, Durable and Non-Durable Goods) decrease in productivity, whereas other sectors increase. Work hours decrease and unit labor costs both increase at the first quarter of 2020.</p></li>
+<li><p>There might be a positive correlation between salary and percentage of employees WFH in the private service providing sector, but not in goods-producing sector. This is consistent with our prediction since goods-producing usually requires employees to be on-site, while service providing does not.</p></li>
 </ul>
 </div>
 <div id="limitations" class="section level2">
@@ -135,13 +136,14 @@ <h2><span class="header-section-number">7.2</span> Limitations</h2>
 <li><p>As we have discussed in the data sources sections, one of the limitation with this study is with gaps within time series data. That post significant challenge for us to take a holistic view of the fluctuation in the WFH employees’ population.</p></li>
 <li><p>Additionally, it would be much better for us to investigate in this topics using real-life datasets that contains specific entries for individual employees. However, due to privacy reasons, that is not realistic for now.</p></li>
 <li><p>Quarterly summarized data is not representative enough for visualization. For future studying, we will try to get more detailed data.</p></li>
+<li><p>We cannot draw a causal effect conclusion on the questions that we were looking at, because these are observational data and there is no control group.</p></li>
 </ul>
 </div>
 <div id="future-directions" class="section level2">
 <h2><span class="header-section-number">7.3</span> Future Directions</h2>
 <p>Several directions to consider looking into in our future research:</p>
 <ul>
-<li><p>Due to time limitation, in this project we only focused on the U.S employment records. In fact, COVID-19 as a global pandemic, has also posted huge influence on the working patterns for various countries around the globe. It might be a good direction to investigate in topics such as: Does WFH employees’ ratio dependent on different countries or regions?</p></li>
+<li><p>Due to time limitation, in this project we only focused on the U.S employment records. In fact, COVID-19 as a global pandemic has also posted huge influence on the working patterns for various countries around the globe. It might be a good direction to investigate in topics such as: Does WFH employees’ ratio dependent on different countries or regions?</p></li>
 <li><p>After studying the potential relationship between teleworking mode and productivity, we want to figure out the reason why productivity decrease in Manufacturing, Durable and Non-Durable Goods sectors. Hence we need to analyze the relationships between these three sectors and factory working hours.</p></li>
 </ul>
 

docs/interactive-component.html

@@ -204,6 +204,10 @@ <h1><span class="header-section-number">Chapter 6</span> Interactive component</
 </button>
 </p>
 <script src="scripts/interactive_bar.js"></script>
+<p>
+The interactive bar graph shows the total number of Work From Home employees change in 2020 by month.
+Click on the buttons, we can explore that each sector has the lowest rate of Work From Home employees in October.
+</p>
 
 </div>
             </section>

docs/reference-keys.txt

@@ -16,8 +16,6 @@ relationship-between-producitivity-and-work-from-home-employees
 part-iii-employment-and-earnings
 employee-numbers
 average-weekly-working-hours-and-overtime-hours
-weekly-working-hours
-weekly-overtime-hours
 average-hourly-earnings
 interactive-component
 conclusion

docs/results.html

@@ -159,20 +159,18 @@ <h3><span class="header-section-number">5.2.4</span> Relationship between Produc
 <h2><span class="header-section-number">5.3</span> Part III: Employment and earnings</h2>
 <div id="employee-numbers" class="section level3">
 <h3><span class="header-section-number">5.3.1</span> Employee numbers</h3>
-<p><img src="finalproj_files/figure-html/unnamed-chunk-29-1.png" width="672" /><img src="finalproj_files/figure-html/unnamed-chunk-29-2.png" width="672" /><img src="finalproj_files/figure-html/unnamed-chunk-29-3.png" width="672" /><img src="finalproj_files/figure-html/unnamed-chunk-29-4.png" width="672" /><img src="finalproj_files/figure-html/unnamed-chunk-29-5.png" width="672" /><img src="finalproj_files/figure-html/unnamed-chunk-29-6.png" width="672" /></p>
-<p>From the time series plot for different sectors and sub-sectors, we can see that for all the industries, there was an abrupt drop in employees number at the beginning of 2020, around the time of March when the pandemic started spreading across the US. The only industry that did not fluctuate much is <code>Utilities</code>. This shows that this industry provides stable jobs.</p>
+<p><img src="finalproj_files/figure-html/unnamed-chunk-29-1.png" width="672" /><img src="finalproj_files/figure-html/unnamed-chunk-29-2.png" width="672" /></p>
+<p>From the time series plot for different sub-sectors, we can see that for all the industries, there was an abrupt drop in employees number at the beginning of 2020, around the time of March when the pandemic started spreading across the US. The only industry that did not fluctuate much is Utilities. This shows that this industry provides stable jobs.</p>
 </div>
 <div id="average-weekly-working-hours-and-overtime-hours" class="section level3">
 <h3><span class="header-section-number">5.3.2</span> Average weekly working hours and overtime hours</h3>
-<div id="weekly-working-hours" class="section level4">
-<h4><span class="header-section-number">5.3.2.1</span> weekly working hours</h4>
-</div>
-<div id="weekly-overtime-hours" class="section level4">
-<h4><span class="header-section-number">5.3.2.2</span> Weekly overtime hours</h4>
-</div>
+<p><img src="finalproj_files/figure-html/unnamed-chunk-33-1.png" width="672" /><img src="finalproj_files/figure-html/unnamed-chunk-33-2.png" width="672" /><img src="finalproj_files/figure-html/unnamed-chunk-33-3.png" width="672" /></p>
+<p>Looking at the first graph, we can see that in general there’s a decrease in weekly working hours at the beginning of pandemic, then the hours started to increase to a new high point. Then by checking the the subsectors, it’s clear that the weekly hours for industries in goods-producing sector dropped while that for industries in private service providing sector increased since the pandemic started. When looking at the hours worked for Utilities, we can see a gradual increase. This may be the result of more people working from home causing higher needs for maintenance.</p>
 </div>
 <div id="average-hourly-earnings" class="section level3">
 <h3><span class="header-section-number">5.3.3</span> Average hourly earnings</h3>
+<p><img src="finalproj_files/figure-html/unnamed-chunk-37-1.png" width="672" /><img src="finalproj_files/figure-html/unnamed-chunk-37-2.png" width="672" /></p>
+<p>From these two graphs, it’s apparent that the there’s an inflation in earnings per hour after the pandemic started, and it’s more obvious in the Private Service Providing sector. Recall that the average weekly working hours in goods-producing sector decreased while that in Private Service Providing sector, we can conclude that the employees in the Private Service Providing sector get higher payrolls after Covid-19 started spreading. Recall again from part 1 that the proportion of WFH increased since Covid-19, it’s possible that there is a positive relationship between the proportion of WFH and payrolls in the Private Service Providing sector.</p>
 
 </div>
 </div>