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<h2 class="hd hd-2 unit-title">Definition of Data Science</h2>
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<p><strong>Learning objectives</strong></p>
<p>In this section you will learn about: </p>
<ul>
<li>The key ingredients for successful collaboration in data science</li>
<li>The evaluation of machine learning systems using an example from radio astronomy</li>
</ul>
<p></p>
</div>
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<p><span style="color: #313131; font-family: 'Open Sans', 'Helvetica Neue', Helvetica, Arial, sans-serif;">The videos in this unit are presented by:</span></p>
<p><span color="#313131" face="Open Sans, Helvetica Neue, Helvetica, Arial, sans-serif" style="color: #313131; font-family: 'Open Sans', 'Helvetica Neue', Helvetica, Arial, sans-serif;">Kiri Wagstaff<br /></span>National Aeronautics and Space Administration (NASA)</p>
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<h3 class="hd hd-2">What is Data Analysis?</h3>
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<h5 style="text-rendering: optimizelegibility; margin-top: 20px; margin-right: 0px; margin-left: 0px; padding: 0px; border: 0px; outline: 0px; font-variant-numeric: inherit; font-variant-east-asian: inherit; font-stretch: inherit; font-size: 16px; font-family: 'Open Sans', 'Helvetica Neue', Helvetica, Arial, sans-serif; vertical-align: baseline; color: #313131;"><span color="#313131" face="Open Sans, Helvetica Neue, Helvetica, Arial, sans-serif" style="color: #313131; font-family: 'Open Sans', 'Helvetica Neue', Helvetica, Arial, sans-serif;">Definition of Data Science</span></h5>
<p style="text-rendering: optimizelegibility; margin-top: 20px; margin-right: 0px; margin-left: 0px; padding: 0px; border: 0px; outline: 0px; font-variant-numeric: inherit; font-variant-east-asian: inherit; font-stretch: inherit; font-size: 16px; font-family: 'Open Sans', 'Helvetica Neue', Helvetica, Arial, sans-serif; vertical-align: baseline; color: #313131;">Data science is an inter-disciplinary field that uses scientific techniques from statistics and computer science to systematically extract knowledge from data.</p>
<p style="text-rendering: optimizelegibility; margin-top: 20px; margin-right: 0px; margin-left: 0px; padding: 0px; border: 0px; outline: 0px; font-variant-numeric: inherit; font-variant-east-asian: inherit; font-stretch: inherit; font-size: 16px; font-family: 'Open Sans', 'Helvetica Neue', Helvetica, Arial, sans-serif; vertical-align: baseline; color: #313131;">In this section, we cover some of the important steps for successful data analysis:</p>
<ol style="text-rendering: optimizelegibility; border: 0px; outline: 0px; font-variant-numeric: inherit; font-variant-east-asian: inherit; font-stretch: inherit; line-height: 1.4em; font-family: 'Open Sans', 'Helvetica Neue', Helvetica, Arial, sans-serif; vertical-align: baseline; color: #313131;">
<li style="text-rendering: optimizelegibility; margin-top: 0px; margin-right: 0px; margin-left: 0px; padding: 0px; border: 0px; outline: 0px; font-style: inherit; font-variant: inherit; font-weight: inherit; font-stretch: inherit; font-size: inherit; line-height: 1.4em; font-family: inherit; vertical-align: baseline;">Developing a shared language</li>
<li style="text-rendering: optimizelegibility; margin-top: 0px; margin-right: 0px; margin-left: 0px; padding: 0px; border: 0px; outline: 0px; font-style: inherit; font-variant: inherit; font-weight: inherit; font-stretch: inherit; font-size: inherit; line-height: 1.4em; font-family: inherit; vertical-align: baseline;">Adequate representation and justification of data</li>
<li style="text-rendering: optimizelegibility; margin-top: 0px; margin-right: 0px; margin-left: 0px; padding: 0px; border: 0px; outline: 0px; font-style: inherit; font-variant: inherit; font-weight: inherit; font-stretch: inherit; font-size: inherit; line-height: 1.4em; font-family: inherit; vertical-align: baseline;">Getting to know your data</li>
<li style="text-rendering: optimizelegibility; margin-top: 0px; margin-right: 0px; margin-left: 0px; padding: 0px; border: 0px; outline: 0px; font-style: inherit; font-variant: inherit; font-weight: inherit; font-stretch: inherit; font-size: inherit; line-height: 1.4em; font-family: inherit; vertical-align: baseline;">Dealing with missing data</li>
<li style="text-rendering: optimizelegibility; margin-top: 0px; margin-right: 0px; margin-left: 0px; padding: 0px; border: 0px; outline: 0px; font-style: inherit; font-variant: inherit; font-weight: inherit; font-stretch: inherit; font-size: inherit; line-height: 1.4em; font-family: inherit; vertical-align: baseline;">Valid ranges of features</li>
<li style="text-rendering: optimizelegibility; margin-top: 0px; margin-right: 0px; margin-left: 0px; padding: 0px; border: 0px; outline: 0px; font-style: inherit; font-variant: inherit; font-weight: inherit; font-stretch: inherit; font-size: inherit; line-height: 1.4em; font-family: inherit; vertical-align: baseline;">Evaluating analyses</li>
</ol>
<p></p>
<p></p>
<p>Suggested Readings:</p>
<ol style="text-rendering: optimizelegibility; border: 0px; outline: 0px; font-variant-numeric: inherit; font-variant-east-asian: inherit; font-stretch: inherit; line-height: 1.4em; font-family: 'Open Sans', 'Helvetica Neue', Helvetica, Arial, sans-serif; vertical-align: baseline; color: #313131;">
<li style="text-rendering: optimizelegibility; margin-top: 0px; margin-right: 0px; margin-left: 0px; padding: 0px; border: 0px; outline: 0px; font-style: inherit; font-variant: inherit; font-weight: inherit; font-stretch: inherit; font-size: inherit; line-height: 1.4em; font-family: inherit; vertical-align: baseline;"><a href="https://www.tandfonline.com/doi/full/10.1080/10618600.2017.1384734" target="[object Object]" style="text-rendering: optimizelegibility; background: transparent; margin: 0px; padding: 0px; border: 0px; outline: 0px; font-style: inherit; font-variant: inherit; font-weight: inherit; font-stretch: inherit; font-size: inherit; line-height: 1.4em; font-family: inherit; vertical-align: baseline; transition: color 0.25s ease-in-out 0s; text-decoration-line: none; color: #0075b4;">Donoho D. 50 years of data science. Journal of Computational and Graphical Statistics. 2017 Oct 2;26(4):745-66. </a></li>
<li style="text-rendering: optimizelegibility; margin-top: 0px; margin-right: 0px; margin-left: 0px; padding: 0px; border: 0px; outline: 0px; font-style: inherit; font-variant: inherit; font-weight: inherit; font-stretch: inherit; font-size: inherit; line-height: 1.4em; font-family: inherit; vertical-align: baseline;"><a href="https://www.pnas.org/content/114/33/8689.long" target="[object Object]" style="text-rendering: optimizelegibility; background: transparent; margin: 0px; padding: 0px; border: 0px; outline: 0px; font-style: inherit; font-variant: inherit; font-weight: inherit; font-stretch: inherit; font-size: inherit; line-height: 1.4em; font-family: inherit; vertical-align: baseline; transition: color 0.25s ease-in-out 0s; text-decoration-line: none; color: #0075b4;">Blei DM, Smyth P. Science and data science. Proceedings of the National Academy of Sciences. 2017 Aug 15;114(33):8689-92. </a></li>
</ol>
</div>
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<h2 class="hd hd-2 unit-title">Developing A Shared Language</h2>
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<p>Key Points:</p>
<ul>
<li>Same words can have different meanings, depending on the context</li>
<li>Define terms/jargon when working in multidisciplinary teams to avoid confusion and errors</li>
</ul>
</div>
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<p>Key points:</p>
<ul>
<li>There is not one single correct way to represent your data - it depends on the nature of the data and the aims of your project</li>
<li>The way the data are represented may limit what conclusions you can draw from your data</li>
<li>Knowing why a model behaves the way it does is also important beyond just performance metrics</li>
</ul>
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<h2 class="hd hd-2 unit-title">Get To Know Your Data</h2>
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<p>Key points: </p>
<ul>
<li>Know what the valid ranges for your data are</li>
<li>Inspect your data to see if there are values that don't make sense</li>
<li>If there are unusual values, check with those who collected the data or handled the instruments that collected the data</li>
</ul>
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<h2 class="hd hd-2 unit-title">Dealing With Missing Data</h2>
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<p>Key points:</p>
<ul>
<li>Inspect your data to determine if there is missing data. Sometimes, missing data is coded as "99999"</li>
<li>Why is the data missing? This requires you to know how the data was collected</li>
<li>Sometimes, missing data arises because a value is unmeasurable (e.g. eccentricity cannot be calculated for a point such as a star)</li>
<li>Don't just blindly fill ("impute") the missing values without first understanding why the value is missing</li>
</ul>
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Unit Exercise
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<legend id="e17d1ab2eb484b45898f9e691e9ef70e_2_1-legend" class="response-fieldset-legend field-group-hd">What are different ways of handling missing data? Check all that apply.</legend>
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<input type="checkbox" name="input_e17d1ab2eb484b45898f9e691e9ef70e_2_1[]" id="input_e17d1ab2eb484b45898f9e691e9ef70e_2_1_choice_0" class="field-input input-checkbox" value="choice_0"/><label id="e17d1ab2eb484b45898f9e691e9ef70e_2_1-choice_0-label" for="input_e17d1ab2eb484b45898f9e691e9ef70e_2_1_choice_0" class="response-label field-label label-inline" aria-describedby="status_e17d1ab2eb484b45898f9e691e9ef70e_2_1"> Imputation
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<input type="checkbox" name="input_e17d1ab2eb484b45898f9e691e9ef70e_2_1[]" id="input_e17d1ab2eb484b45898f9e691e9ef70e_2_1_choice_1" class="field-input input-checkbox" value="choice_1"/><label id="e17d1ab2eb484b45898f9e691e9ef70e_2_1-choice_1-label" for="input_e17d1ab2eb484b45898f9e691e9ef70e_2_1_choice_1" class="response-label field-label label-inline" aria-describedby="status_e17d1ab2eb484b45898f9e691e9ef70e_2_1"> Replacing with random numbers
</label>
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<input type="checkbox" name="input_e17d1ab2eb484b45898f9e691e9ef70e_2_1[]" id="input_e17d1ab2eb484b45898f9e691e9ef70e_2_1_choice_2" class="field-input input-checkbox" value="choice_2"/><label id="e17d1ab2eb484b45898f9e691e9ef70e_2_1-choice_2-label" for="input_e17d1ab2eb484b45898f9e691e9ef70e_2_1_choice_2" class="response-label field-label label-inline" aria-describedby="status_e17d1ab2eb484b45898f9e691e9ef70e_2_1"> Offsetting the normal range
</label>
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<h2 class="hd hd-2 unit-title">Valid Ranges of Features</h2>
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<p>Key points:</p>
<ol>
<li>Know the units of measurements</li>
<li>Consider converting variables to the same time units </li>
<li>Certain features might be more important than others based on prior knowledge - you may use this knowledge to weigh your analysis</li>
</ol>
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<h2 class="hd hd-2 unit-title">Evaluating Analyses</h2>
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<p>Key points:</p>
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<li>Evaluate your system based on how others will be using it</li>
<li>Some classification errors by a model might have greater implications than others (e.g. predicting someone will die when they actually live vs. predicting someone will live when they actually die)</li>
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<legend id="4a7d470a622740c3a8598e80409aa41d_2_1-legend" class="response-fieldset-legend field-group-hd">Which of the following is an example of a binary prediction problem?</legend>
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<p>Key Points:</p>
<ul>
<li>Key ingredients for successful collaboration in data science:</li>
<ul><ol>
<li>Expertise</li>
<li>Shared language</li>
<li>Knowing your data's characteristics</li>
<li>Meaningful evaluation</li>
</ol></ul>
<li>These are the prerequisites to foster the discovery and translation of findings into real-world applications</li>
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</div>
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<h2 class="hd hd-2 unit-title">End of Subsection 1.1: Quiz</h2>
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Question 1
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<legend id="6dd25892e8494ce997dbb9359e004e59_2_1-legend" class="response-fieldset-legend field-group-hd">Which of the following is NOT part of good data science?</legend>
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Question 2
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<legend id="07baa9f1abf24ca5b07629be089ee708_2_1-legend" class="response-fieldset-legend field-group-hd">Why is it important to develop a shared language? Check all that apply.</legend>
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<input type="checkbox" name="input_07baa9f1abf24ca5b07629be089ee708_2_1[]" id="input_07baa9f1abf24ca5b07629be089ee708_2_1_choice_1" class="field-input input-checkbox" value="choice_1"/><label id="07baa9f1abf24ca5b07629be089ee708_2_1-choice_1-label" for="input_07baa9f1abf24ca5b07629be089ee708_2_1_choice_1" class="response-label field-label label-inline" aria-describedby="status_07baa9f1abf24ca5b07629be089ee708_2_1"> Researchers should only use one programming language to perform analyses
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<input type="checkbox" name="input_07baa9f1abf24ca5b07629be089ee708_2_1[]" id="input_07baa9f1abf24ca5b07629be089ee708_2_1_choice_2" class="field-input input-checkbox" value="choice_2"/><label id="07baa9f1abf24ca5b07629be089ee708_2_1-choice_2-label" for="input_07baa9f1abf24ca5b07629be089ee708_2_1_choice_2" class="response-label field-label label-inline" aria-describedby="status_07baa9f1abf24ca5b07629be089ee708_2_1"> Certain terminology can have a negative connotation
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Question 3
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<legend id="c131c51cc01145ff8068a25eb6e09041_2_1-legend" class="response-fieldset-legend field-group-hd">What is the best strategy to handle outliers or missing values?</legend>
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<input type="radio" name="input_c131c51cc01145ff8068a25eb6e09041_2_1" id="input_c131c51cc01145ff8068a25eb6e09041_2_1_choice_0" class="field-input input-radio" value="choice_0"/><label id="c131c51cc01145ff8068a25eb6e09041_2_1-choice_0-label" for="input_c131c51cc01145ff8068a25eb6e09041_2_1_choice_0" class="response-label field-label label-inline" aria-describedby="status_c131c51cc01145ff8068a25eb6e09041_2_1"> Set them to zero
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<input type="radio" name="input_c131c51cc01145ff8068a25eb6e09041_2_1" id="input_c131c51cc01145ff8068a25eb6e09041_2_1_choice_1" class="field-input input-radio" value="choice_1"/><label id="c131c51cc01145ff8068a25eb6e09041_2_1-choice_1-label" for="input_c131c51cc01145ff8068a25eb6e09041_2_1_choice_1" class="response-label field-label label-inline" aria-describedby="status_c131c51cc01145ff8068a25eb6e09041_2_1"> Replace them with imputed values
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<input type="radio" name="input_c131c51cc01145ff8068a25eb6e09041_2_1" id="input_c131c51cc01145ff8068a25eb6e09041_2_1_choice_2" class="field-input input-radio" value="choice_2"/><label id="c131c51cc01145ff8068a25eb6e09041_2_1-choice_2-label" for="input_c131c51cc01145ff8068a25eb6e09041_2_1_choice_2" class="response-label field-label label-inline" aria-describedby="status_c131c51cc01145ff8068a25eb6e09041_2_1"> Replace them with the average
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<input type="radio" name="input_c131c51cc01145ff8068a25eb6e09041_2_1" id="input_c131c51cc01145ff8068a25eb6e09041_2_1_choice_3" class="field-input input-radio" value="choice_3"/><label id="c131c51cc01145ff8068a25eb6e09041_2_1-choice_3-label" for="input_c131c51cc01145ff8068a25eb6e09041_2_1_choice_3" class="response-label field-label label-inline" aria-describedby="status_c131c51cc01145ff8068a25eb6e09041_2_1"> Seek input from domain expert (e.g. clinician)
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Question 4
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Question 5
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