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Merge pull request #60 from UBC-DSCI/ml_inference
Ch 11 - Inference
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01-reading.Rmd

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We can also use `read_csv()` or `read_delim()` (and related functions) to read in tabular data directly from a url that contains tabular data. In this case, we provide the url to `read_csv()` as the path to the file instead of a path to a local file on our computer. Similar to when we specify a path on our local computer, here we need to surround the url by quotes. All other arguments that we use are the same as when using these functions with a local file on our computer.
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```{r}
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us_data <- read_csv("https://raw.githubusercontent.com/UBC-DSCI/introduction-to-datascience/master/state_property_vote.csv")
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us_data <- read_csv("https://raw.githubusercontent.com/UBC-DSCI/introduction-to-datascience/master/data/state_property_vote.csv")
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us_data
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```
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10-inference.Rmd

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data/listings.csv

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docs/GitHub.html

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<meta name="author" content="Melissa Lee" />
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<meta name="date" content="2020-09-03" />
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<meta name="date" content="2020-11-03" />
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<meta name="viewport" content="width=device-width, initial-scale=1" />
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<meta name="apple-mobile-web-app-capable" content="yes" />
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<li class="chapter" data-level="10.5" data-path="clustering.html"><a href="clustering.html#k-means-in-r"><i class="fa fa-check"></i><b>10.5</b> K-means in R</a></li>
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<li class="chapter" data-level="10.6" data-path="clustering.html"><a href="clustering.html#additional-readings"><i class="fa fa-check"></i><b>10.6</b> Additional readings:</a></li>
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</ul></li>
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<li class="chapter" data-level="11" data-path="inference.html"><a href="inference.html"><i class="fa fa-check"></i><b>11</b> Introduction to Statistical Inference</a><ul>
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<li class="chapter" data-level="11.1" data-path="inference.html"><a href="inference.html#overview-9"><i class="fa fa-check"></i><b>11.1</b> Overview</a></li>
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<li class="chapter" data-level="11.2" data-path="inference.html"><a href="inference.html#chapter-learning-objectives-9"><i class="fa fa-check"></i><b>11.2</b> Chapter learning objectives</a></li>
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<li class="chapter" data-level="11.3" data-path="inference.html"><a href="inference.html#why-do-we-need-sampling"><i class="fa fa-check"></i><b>11.3</b> Why do we need sampling?</a></li>
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<li class="chapter" data-level="11.4" data-path="inference.html"><a href="inference.html#sampling-distributions"><i class="fa fa-check"></i><b>11.4</b> Sampling distributions</a><ul>
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<li class="chapter" data-level="11.4.1" data-path="inference.html"><a href="inference.html#sampling-distributions-for-proportions"><i class="fa fa-check"></i><b>11.4.1</b> Sampling distributions for proportions</a></li>
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<li class="chapter" data-level="11.4.2" data-path="inference.html"><a href="inference.html#sampling-distributions-for-means"><i class="fa fa-check"></i><b>11.4.2</b> Sampling distributions for means</a></li>
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<li class="chapter" data-level="11.4.3" data-path="inference.html"><a href="inference.html#summary-1"><i class="fa fa-check"></i><b>11.4.3</b> Summary</a></li>
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</ul></li>
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<li class="chapter" data-level="11.5" data-path="inference.html"><a href="inference.html#bootstrapping"><i class="fa fa-check"></i><b>11.5</b> Bootstrapping</a><ul>
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<li class="chapter" data-level="11.5.1" data-path="inference.html"><a href="inference.html#overview-10"><i class="fa fa-check"></i><b>11.5.1</b> Overview</a></li>
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<li class="chapter" data-level="11.5.2" data-path="inference.html"><a href="inference.html#bootstrapping-in-r"><i class="fa fa-check"></i><b>11.5.2</b> Bootstrapping in R</a></li>
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<li class="chapter" data-level="11.5.3" data-path="inference.html"><a href="inference.html#using-the-bootstrap-to-calculate-a-plausible-range"><i class="fa fa-check"></i><b>11.5.3</b> Using the bootstrap to calculate a plausible range</a></li>
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</ul></li>
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<li class="chapter" data-level="11.6" data-path="inference.html"><a href="inference.html#additional-readings-1"><i class="fa fa-check"></i><b>11.6</b> Additional readings</a></li>
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</ul></li>
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<li class="divider"></li>
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<li><a href="https://github.com/rstudio/bookdown" target="blank">Published with bookdown</a></li>
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