Sunday, May 3, 2020

Review: TP-Link AC2600 Range Extender 650 Wifi Extender

This is my review of the TP-Link AC2600 Range Extender 650 Wifi Extender.

Spotty Connectivity was Cramping my WFH Style

I recently decided I needed to improve my work-from-home Internet situation. I work for a big tech company (Amazon) and fast, reliable connectivity is something I need to have every day. With multiple family members spending a lot of time streaming and conferencing, we needed more bandwidth. Most important of all, I needed to resolve the poor connectivity from my home office to the family room where our fiber modem is. On some days I would lose connectivity every few minutes during business hours, which is particularly maddening during a video meeting.

To combat the bandwidth problems my wife Becky got on the phone with our Internet provider Frontier and worked wonders. She not only secured the maximum bandwidth available (for only $5/month more!) but also scored an equipment upgrade for the modem. A speed check on was showing 80 Mbps near the router but I was getting only 10-15 Mbps in my home office. That went up a bit after the bandwidth upgrade but was still a far cry from what it should be. To reach my home office I would need a wifi extender, but which one? I read up a bit on wifi extenders and ordered the TP-Link AC2600 Range Extender 650 from Amazon for $108.

Enter the TP-Link RE650

I received the RE650 4 days after ordering it and rushed to unpack it and set it up. I had the notion this would be a pair of devices with an Ethernet cable, but it's actually just a single unit that you plug into an outlet and no cables are needed. There are two flip-up flat antennae on either side.


My first impression of the RE650 was that it strongly reminded me of The PKE Meter in the 1984 movie Ghostbusters! After prancing around the house pretending I was Egon for a few minutes, I returned to the serious business of setting up our new wifi extender.

Wifi Extender or Specter Detector? You Decide


The RE650 comes with an easy setup that is nicely documented and there are several ways to configure it: with a phone app, by pressing the WPS button available on some routers, or using your computer. I chose the latter. You initially plug in the unit near your router and wait for the power light to appear. A new wifi network appears that you can connect to for a web-based configuration. The configuration experience is very simple with just a few pages.

The quick setup lists your detected wifi networks, from which I was able to select my router's 2.4GHz and 5GHz networks and provide their passwords. You then name your new wifi extender networks. Be careful here, the setup program will default to the same names as your router's networks and I found that a little confusing. You almost certainly want new names to distinguish your wifi extender networks from the original networks.

I expected to be able to set new passwords for the extended wifi networks but apparently that's not an option and you keep using your original network passwords; perhaps that's intentional for security.  Once you have the configuration done, you connect to the new wifi extender networks and confirm setup is complete.

Despite the overall good quick setup design, it did take me 3 attempts to configure the RE650 and I started over twice with a factory reset (you use a pin for that).

Finding the Optimal Location

With the RE650 configured, you then unplug it and find a home for it about halfway between the router and the dead zone you want to extend coverage to. That means reviewing where your outlets are and trying to find your best option.

Although I didn't use it for setup, I did install the phone app afterward which is handy. It includes a Location Assistant tool for checking signal strength. I had three places to choose from, found the best one, and that was that.

A speed test from my home office (on the 5G wifi extender network) now shows 70-80 Mbps, an amazing improvement from the 10-15 Mbps I was seeing a week ago. Best of all, I don't have spotty connectivity anymore. Depending on what you're used to you may not consider 80mbps all that speedy— some of my co-workers have ten times that!— but I live in a rural area and have limited options. I'm fortunate to be on fiber.

Before and After: a huge improvement

Day 1: Life is Good

My first day on the new setup was fantastic. I stayed connected and enjoyed much higher speed than I'd ever had from my home office. If only things stayed that way...

Day 2: Connectivity, Interrupted

On Day 2 that all changed. I had 4 hours of video conferences and they were terrible: garbled video/audio and dropped connections. Connectivity was constantly dropping. I couldn't understand how this could be since the prior day had been so perfect.

I researched what others were saying about the RE650, specifically around connectivity interruptions. A number of people had experienced the same things, and many of them ended up returning the range extended; had I made a mistake? I kept researching. There was advice to change the channel and channel width on the main router. I'd never really worked with routers to that level but I learned how to access my router and view/edit its settings. For the 5GHz network, channel was set to Automatic. Perhaps there was interference from a neighbor? I reviewed the ports available in setup and chose the highest port at random, 165. Then I reconnected to the wife extended to see how things were. I watched Twitch for an hour to see if there would be any video interruptions. I stayed connected, which was reassuring, but I also saw bandwidth was lower: a speed test showed I was now in the 30-40 range. I'd lost half my speed.

More research. Channel width lets you increase throughput. My router admin UI said the channel width was 20, but I'd heard routers could do 40 or even 80 in 5GHz. I didn't see a way to set width, however. Finally I tried changing to a different channel, 36, and the UI now showed a width of 80. I reconnected to my extended wifi network and ran 100mbps! the highest I had seen yet from my home office. But, how was connectivity? I watched video on Twitch for 90 minutes and didn't have any connection loss. Promising, but the real test would be videoconferencing at work the next day.

In summary, the RE650 is a nicely-designed, easy to install wifi extender that works well. If you need to extend your wifi to a dead zone or improve spotty connectivity, it's a good choice.

Saturday, May 2, 2020

Bad Charting Part 4: Following Conventions

This is Part 4 in a series on avoiding the pitfalls of bad charting. In this final post of the series we'll look at the importance of following conventions in charts, including use of color and the use of 3D in charts.


Conventions. Without them, useful communication is impossible: humans couldn't converse, publish, collaborate, or have discourse (civil or otherwise) without conventions. And so it is with charts: fail to follow conventions, and you'll be sending the wrong message. If you're digesting a chart prepared by someone else, be on the lookout for flouting conventions: it's one of the ways a chart can be rigged to send a contrary message to the story the data tells. In Part 1, we mentioned how makers of infographics often don't feel constrained to "follow the rules" in their charts. Violating conventions is one of the chief offenses.

Directional Flow

The flow of things on your chart, including arrows, should conform to the culture of your audience. For example, the following are deeply ingrained in Western culture, to the point where few people even bother to think about them consciously: they're just understood.

Time moves left to right, always. Going up means more, gain, or north; down means less, loss, or south. Fail to follow these conventions, and people will struggle to understand your visuals. Targeting a different culture than yours? Do your research and find out what they consider normal.

Here's the most egregious example I know of ignoring conventions. What does this chart make you conclude about the effect of Florida's "Stand Your Ground" law? Gun deaths appear to drop rapidly after 2005.

Now think about what we covered previously about the importance of accurate chart axes, and take a look at the Y axis tick markings: they're upside down! This chart is effectively inverted, because it fails to follow the convention that up means more.

On a Map, Darker Map Shades Mean More

Consider a map that is conveying data, such as which US states make the most revenue. The convention is that darker shades mean more (greater density or higher amounts).

In the map chart below, darker blue shades were used for lower export profits and lighter green for higher. It's the opposite from most maps of this kind. This doesn't make the chart evil, but it is flouting a convention. If the shading scale was reversed, readers would get what the map is trying to convey more readily. Every time you go against a convention, you up the chance someone will get the wrong message.

Use of Color

If you're just trying to select two colors for showing last month's expenses vs. this month's expenses, color choice might not seem very important, but it can be. It helps to understand how your audience perceives color so you can use it to support the story your chart is telling. We'll talk about some of the meanings attached to colors by different groups. First though you should understand that it's a mistake to rely solely on color to communicate something: a substantial number of people are colorblind (and many don't even know it). Always accompany color with other visual cues. Here's how a colored chart might appear to a colorblind person:

Color might appear to be one of those worldwide or east/west cultural matters, as in "Western culture associates red with danger"—and it is, to some degree. Then again, red is often used to communicate other things like excitement or Communism to that same audience. 

Like most things, going extreme in color will make your chart worse, not better. Avoid too many colors or strong saturated hues: it's the color graphics equivalent of shouting. If you practice restraint in your general color palette, then you can highlight something really effectively with a stronger color.In the two charts below, is the color chart on the left easier or harder to perceive than the grayscale version to the right? I find the color chart loud and ugly with colors that distract rather than help. The grayscale chart is effective without the color.

Different groups attach different meanings to color, known as Color Biases. Speaking broadly, western culture audience will attach any of these associations to colors:
  • Blue: trust, security, peace, coolness
  • Green: nature, freshness, luck, environment, wealth, inexperience, jealousy
  • Orange: warmth, harvest, light, heat
  • Purple: power, royalty, ambition, independence
  • Red: warmth, excitement, passion, love, danger
  • Yellow: joy, value, sunlight, caution, cowardice

We can't stop there however. Many industries also have color biases, and failing to know that could really upset how chart colors will hit your audience.You might be inclined to use green for good things and red for bad, but to someone in health care green means infected and red means healthy! It's worth getting to know your audience, and one easy way to do that is to examine how charts in their industry are commonly colored and labelled.
  • In Finance: blue is reliable/subdued, green is profitable, yellow is highlighted/important, red is unprofitable
  • In Health Care: blue is dead, green is infected, yellow is jaundiced, red is healthy
  • To Control Engineers, blue means cold/water, green is safe, yellow is caution, red is danger


There's only one rule for using 3D in your charts and it's very simple: don't do it, ever. Why, you ask? Making that bar chart or pie chart into 3D adds a nice touch, you might argue. Let's see. Look at the two pie charts below. Who sold the most in Q1? And who sold the most in Q2? When I asked this question the last time I presented on charting, many people said Paul (blue) sold the most in Q1 and Bryan (orange) sold the most in Q2. 

In fact, these are two pie charts of the same data (below), simply with a different rotation. Paul and Bryan have exactly the same sales. The 3D effects break the visual contract that normally gives a pie chart its power: your eye and brain interpreting the relative proportions of the visual elements. That's completely demolished by a 3D pie chart. There's no greater evil in the charting world.

In the 3D column chart below, your first impulse is to see the green 1997 value as way smaller than the red 1995 value. You can intellectually understand there's perspective in the graphic, but a reader's first take on the chart is still going to be misleading.

3D column chart

There's simply nothing to be gained by making your charts 3D. Promise me you won't do it.


This series was inspired by the first resource I came across about deceptive charting, How to Lie with Charts by Gerald Everett Jones. Now in its fourth edition, Gerald has kept his book current with new material on topics like fake news and social media disinformation.

Well, that's it for this series. I hope you now feel well-equipped to detect misleading charts when you encounter them, and to avoid being misleading in the charts you create.

Sunday, March 8, 2020

Bad Charting Part 3: Axis Abuse

This is Part 3 in a series on avoiding the pitfalls of bad charting. Today we'll discuss how axis abuse can make a chart deceptive.

Axis Abuse: What Is It?

Axis abuse happens when your chart's axes (such as the X-axis or Y-axes for a bar chart) don't follow standard conventions. Those conventions include starting your axis at 0, using a proper aspect ratio, and using an expected axis range. Axis abuse is unbelievably common, and that's because it's one of the easiest and most effective ways to distort how a chart is understood.

Axes Should Start at Zero

When charts show amounts with a visual element (such as bar, column, line, area, and pie charts), there's an implicit assumption that we are being shown the whole thing. When it turns out we're only seeing part of the picture, we're being deceived. The way we're all taught to understand charts with axes is that the bottom left corner is zero. When a chart fails to uphold that, we get the wrong idea about what's being shown. Let's look at some examples.

Example 1: Emissions

Look at the chart below. Taking in what the visuals portray, how do you feel about Emission A vs. Emission B? At first glance, Emission B seems about five times worse than Emission A.

The above chart has a flaw: the Y axis starts at 30, not 0, which paints a deceptive picture. Below is the same data, this time with a correct zero baseline. It tells a very different story, doesn't it? Now we see the truth: Emissions B is more like 1.5 times Emissions A.

Example 2: London Times

Here's an example of a misleading chart in the London Times. The chart—and the whole premise of the article—is about how the Times is outselling the competition. The chart visuals communicate that the Times has more than twice the circulation of the Daily Telegraph. Now look at the Y axis: the chart axis begins at 420,000! If it started at zero, the difference between the Times (485K) and the Daily Telegraph (446K) would be hardly noticeable, a non-story.

The Times Has A Massive Lead in Circulation ..or Does It?

It is unbelievably common for axis abuse to happen in newspapers and magazines. These are organizations that should certainly know better. Be on your guard!

Example 3: Television Sports Chart

Television news networks and sports networks are just as guilty as print media with axis abuse. Look at the screenshot below from a sports program, where R.A. Dickey's Knuckleball Velocity is made to look like it's half of what it used to be. With an honest baseline of zero the drop from 77.3MPH to 75.3MPH would be barely noticeable.

R. A. Dickey's Knuckleball Isn't What It Used To Be...?

Example 4: Average Male Height Increase Over the Years

The chart below is supposed to show how average male height (aged 21) has increased from the 1870s to the 1970s. It looks pretty astonishing; the visuals convey that men have doubled in height over a century! Once again, we have a dishonest baseline that starts at 155cm instead of 0cm.

My, How You've Grown!


Example 5: Server Load

Which server load chart below gives you more concern? By now you realize these two charts are driven by the exact same data. The only difference is that the first chart's Y axis starts at 80 while the second starts at 0.

Which Load Chart Concerns You More?

Example 6: Microsoft Edge Performance

One last example to illustrate how common and audacious this practice is. In the gauge charts below, Microsoft is crowing how Microsoft Edge outperformed Chrome and Firefox in a particular benchmark. While the claim is true, these charts are highly misleading. When you consider that Edge (blue gauge) scored 31,786 while Chrome (green) scored 29,619 and Firefox (red) scored 26,876 it's quite clear these gauges do not start at zero. Even worse than the prior examples, they're not even labelled.

Misleading Browser Charts

If we plotted the benchmark data honestly, it would look like this on a column chart:

 A more Honest Comparison

If You Must Show A Partial Axis...

On occasion you may feel you have a valid reason to truncate an axis. If you feel strongly compelled to not show a complete axis, there are responsible ways to depict that. The chart below makes it clear that the bars are truncated.

A Responsible Way to Show a Partial Axis

Chart with Integrity

All sorts of excuses are made for not starting with a zero baseline. There's not enough space. We want to focus in on the interesting part of the chart. People sit too far from the TV to make out the detail. None of these excuses justify the deception, and it is deception, whether intentional or not. You form a conclusion from the visuals long before (or if) you digest the numbers on the chart.

The widespread practice of deceptive charting does not make it okay. Beware this lack of integrity when you view charts, and don't go down this road with your own charts. Always value honesty and accuracy over getting attention.

Don't Deceive With Ranges

Charts can also be deceptive when the amount of data selected is altered to favor a preferred story. Look at the two stock charts below from Yahoo. Which stock would you rather own, the one in red that's descending or the one in green that's on the way up?

Which Stock Would You Rather Own?

In point of fact, these are both AMZN stock charts take at the same time. The only difference is that the first chart was a 1 Day range of data while the second showed a 1 Year of data.

Never pull the wool over your audience's eyes by selecting an unexpected data range, and never leave out important information like what the interval is. There's a reason public companies have to abide by strict rules and report data over careful intervals like quarters.

Don't Omit Intervals

Another way a chart can be deceptive is when you don't have (or don't include) all of the data intervals. The creator of the chart below didn't have data for 2003 or 2004, so it's not on the chart. But that's deceptive, because it makes it look like the data is trending differently than it really is.

The chart below is better because it makes it clear that some of the data is missing. The viewer is less likely to draw an incorrect conclusion about trends.

Use Proper Aspect Ratios 

Yet another built-in assumption we have when we view charts is that they follow a 45-degree slope. When they don't, we can be fooled into seeing an attractive or scary rate change. Look at the charts below, which show the same data but with varying aspect ratios. They certainly convey different emotions, don't they?

Aspect Ratio Changes the Message


One of the easiest ways to change the message of a chart is by toying with its axes. Axes that don't start at zero mislead because we are seeing only part of amounts in the visuals. Unexpected ranges also mislead because we are seeing less or more of the data than we expect. Improper aspect ratios and missing intervals can deceive us about trends.

Chart makers have a great deal of power. There's a visual contact between chart maker and chart viewer, and as a responsible chart maker you need to be aware of that contract and uphold it.

In Part 4, we'll look at conventions, color, and the use of 3D in charts.

Friday, February 28, 2020

Bad Charting Part 2: Use the Right Chart Type

This is Part 2 in a series on avoiding the pitfalls of bad charting.Today we'll discuss the importance of using the right chart type for what you want to show, and what happens when you get that wrong.

Wrong Chart Type Examples

Before we get how to choose the right chart type, let's see some examples where using the wrong chart type killed the chart's effectiveness. These examples come from the European Environment Agency's Chart Do's and Don'ts site.

Households by Type

Below we see a stacked column chart depicting households by type. Each column totals 100% but is subdivided to break down percentage of various household types. Before going further, do any particular trends jump out at you from this chart?

The Stacked Column Chart is the wrong choice for this datasource: Chart Do's and Don'ts

Now consider the same data below plotted in a line chart. There's a dramatic difference, and now it's easy to see a nosedive in the Married Couples with Children category. In the earlier chart, this was all but unnoticeable. As this chartmaker did, you might make this the chief message of your chart and highlight it.

A Line Chart is a better choice for this data

Specialization in Nordic Labor Markets

In this example, a bubble chart was plotted over a map to show specialization in high-tech manufacturing and/or R&D in Nordic labor markets in 2005 (that's a mouthful). While the use of the map might be useful to someone very familiar with the local geography, the map obscures rather than helps. It's not the simplest way to show the winners and losers.

The Map hinders rather than helps this chart

The simple bar chart below is a lot easier to digest.

A Bar Chart is a better choice for this purpose

These examples show how important it is to use an appropriate chart type.

What is it You Want to Show?

Choosing the right chart type depends on your objective. Why do you want to visualize this data? Do you want to compare something? Show what something is composed of? Show distribution? Show a relationship? Answering this first question will reduce your chart choices from many to a handful.

Once you know your objective, you'll still have several chart types available. You can settle on the right chart type by also considering the number of variables you need to show, whether there are few or many data points, and whether you'll be showing values over time.

A guide such as the Chart Chooser diagram by Dr. Andrew Abela can be helpful. Keep in mind that this is not a definitive list. New chart types arise from time to time and some chart types wax and wane in popularity over time. For example, right now the pie chart has fallen into disfavor in some circles. You might want to prune your options to the chart types your organization is comfortable with.

Chart Chooser

Let's look at these 4 big categories of data visualization and see what makes them tick.


In a comparison you have multiple items to compare or multiple datasets to compare. If you need to show exact values, consider a table in place of a chart.

When you have just a few categories a column chart is a good choice. For example, showing responses to a survey question or comparing sales for the last two years.

 Column Chart

When you have many categories or long names, a horizontal bar chart will work better.

Bar Chart

When you have multiple data series per category, a grouped column chart (also known as a grouped bar chart or a clustered bar graph) may work best. For example, imagine you want to break out responses to a survey question not only by the response given but also by age range.

Grouped Column Chart

To show trends over time for continuous data, use a line chart. For example, illustrating how various categories of expenses are trending over time.

Line Chart


In composition you are revealing what makes up a data set.

To show the composition of something with simple proportions, a pie chart is ideal. They are one of the most widely-understood chart types. Nevertheless there is currently a backlash against pie charts by some so you should carefully consider whether they are a good choice for your audience. You can help the pie chart's reputation by using them properly, that is to show percentages that add up to 100%.

Pie Chart

A donut chart is nothing more than a pie chart with a hole in the center. Any place you can use a pie chart a donut chart would be equally appropriate. One thing a donut chart can do that a pie chart can't do is show multiple data series by arranging multiple concentric rings around each other.

 Donut Chart

When you want to show trends over time combined with part-to-whole composition, you can use an area chart. Area charts have some similarities to line charts but use filled areas below the line. The categories are stacked upon each other instead of all being plotted from the baseline. In Area charts the individual trends are harder to make out. Here's an area chart showing subscription sales over the course of a year, with substrata for students, adults, businesses, and non-profits. We might gain some insights into how school schedules or holidays affect sales.

Area Charts

To show the composition of data across different categories, consider a stacked column chart. In the first chart below, sales revenue of various product categories are decomposed by season.

Stacked Column Chart

When you want to focus on the composition of the data, you can use a stacked column chart and show percentage in the Y-axis. This is sometimes called a Stacked Percent Chart and all columns will be the same height (100%). In the chart below, reusing the same data from the earlier example, apparel revenue percentage is shown, again broken down by season.

Stacked Percent Chart


When you want to show how one variable is related to one or more other variables, consider a scatter plot chart or a bubble chart. Both can all be useful for showing suspected connections between the data.

A scatter plot chart is used to analyze the relationship between two variables (one on each axis). The pattern of intersecting points can highlight a possible relationship. The chart below suggests a relationship between the amount of sugar people eat and their likelihood of tooth decay.

Scatter Plot Chart 
source:  FactTank

A bubble chart is much like a scatter plot chart except it can show a third variable, in the size of each bubble (its area, not its diameter). The bubble chart below shows car sales, with price in the Y-axis, units sold in the X-axis, and revenue in in the bubble. We can tell type B generates the most revenue both by the size of the bubble and its placement.

Bubble Chart

While the above charts are well-suited for relationship visualization, it's also possible to show relationships using more common chart types like line, column, and bar charts.


Distribution charts show how variables are distributed over time, which can help identify trends and outliers.

Use a scatter plot can show the distribution of two variables. The scatter plot chart below shows Old Faithful geyser eruptions. It shows there are short-wait eruptions and long-wait eruptions.

Scatter Plat showing Distribution
source: Wikipedia

A histogram is another way to show distribution of continuous data. Histograms superficially resemble column charts but the columns have no spacing and indicate frequency, not specific values. The X-axis shows interval ranges and the Y-axis shows number of times values occurred. The histogram below shows the majority of customers wait between 35-50 seconds.

Histogram showing Customer Wait Time

Progress Toward Goals

The bullet graph, a 21st century chart, is a nice compact way to show progress toward a goal. These can be vertical or horizontal, and combine the idea of a thermometer chart with red/yellow/green ranges.

Many Variables

Radar Charts, also called Spider Charts, are useful when you have many variables. They let you plot a dozen or more variables and derive a shape from them. Comparing shapes then shows similarity.

In the chart below, attributes of the Overwatch League are plotted (blue shape). On top of that, attributes of the Twitch community are plotted (orange shape). The chart shows similarities in the two shapes, which helps make the case that Twitch is a good streaming home for the Overwatch League.

Radar Chart

source:  the eSports Group

Years back when I worked at Microsoft, we would use radar charts in developer usability studies. We would chart shapes for the developers we tested and compare them to what our APIs provided.


There are many kinds of charts because there are many purposes for visualizing data. We've reviewed some examples of how the wrong chart type obscures rather than clarifies. We learned how to choose the right chart type for your objective and reviewed some of the more common chart types.

In Part 3, we'll look at how Axis Abuse can make your charts misleading.