# Why Do We Need Data?

We use data every day to help make decisions. Which cell phone has the most features for the best price? What were the reviews of the movie we want to see? Does the type of shoe I buy help me play a sport better?

By looking at data and data trends, we can make decisions based upon research rather than taking a guess and hoping for the best.

Look at the slideshow below. Each picture shows different people analyzing data and predicting trends. Look at each picture to see how they are using data.

# What Can Data Tell You?

A rancher raises pigs on his farm. He currently has a total of 20 sows (female pigs). A sow is pregnant for about 4 months and usually gives birth to a litter of 8 to 12 pigs at a time. A sow can have 2 litters each year. The rancher is trying to plan ahead and ensure he has enough space for all his pigs. He wants to estimate the number of piglets he will have over the next year. How many piglets can the rancher expect to have over the next year?

*Source: grateful, Woodleywonderworks, Flickr*

Let's put this information in a data table, so we can take a look at trends.

So, if an average sow can have 20 piglets each year, how many would 20 sows have?

**20 sows x 20 piglets a year = 400 pigs**

What if the rancher buys a few more sows or sells a few? Then, he will no longer have a total of 20. Let's put this information on a graph to see if we can find any trends.

This graph now gives the rancher the ability to predict how many piglets he can expect each year based on the number of sows. If he collected data on the number of piglets each sow actually had, he could see which sow had more offspring than average and which had fewer than average.

Now, he has the ability to make adjustments to the animal feed and to judge when he needs to expand or when he needs to sell some of the sows.

Data is a powerful tool.

# Analyzing Data, Identifying Patterns, and Predicting Trends

A graph can be thought of as a "picture" of data. Graphs are useful because they can reveal patterns or trends and can be used to make predictions. You can analyze and evaluate data found in graphs to make predictions.

- An interpolation is a prediction made between known data points.
- An extrapolation is a prediction made beyond known data points.

Let's look at an example of using data to reveal patterns or* *trends and make predictions.

A student conducted an experiment to determine if the temperature of the water affected the breathing rate of the freshwater sunfish. Temperature was measured in degrees Celsius and breathing rate was per minute. The data table and graph below show the data that was collected. Notice some of the data in the data table is missing.

If you were asked to determine what the breathing rate was when the water was 23 degrees Celsius, you can simply look at the data table or graph to determine the answer. Click on the hotspots to discover the breathing rate.

What is you were asked to determine the breathing rate at 26°C?

You might also be asked to describe the overall trend of the data. To do this you need to look at the graph as a whole and describe what you see. Look at the independent variable and the dependent variable.

**You Try!**

A student was studying the use of fertilizers to promote plant growth in the laboratory. This graph shows her data on one plant. Analyze the data provided in the graph to answer the following questions.

# Practice: Analyzing Data

Directions: Use the graphs and data tables to answer the following questions.

**Data Set A**

A student conducted an experiment to determine if the temperature of the water affected the breathing rate of the freshwater sunfish. Temperature was measured in degrees Celsius and breathing rate was per minute. The data collected is shown below.

**Data Set B**

A student wanted to test to see how temperature affected plant growth. He used the same type of plant, planter, amount of water, and fertilizer. The plants were left in controlled temperature chambers for 40 days, and at the end of 40 days, the height of the plants was measured in centimeters. The data collected is shown below.

**Data Set C**

A siamang gibbon is an ape that lives in the rain forest of Southeast Asia. These gibbons depend on more than 160 species of rain forest trees and other plants for food. Half of the siamang gibbon’s diet comes from leaves. Forty percent of its diet comes from fruits, and the remaining portion of its diet comes from flowers, buds, and insects.