In the science classroom, generating and testing a hypotheses can be utilized easily. Before each experiment I have students make a prediction about the outcome of the experiment based on prior knowledge. They must provide an explanation of how or why they came up with their conclusion. After the lab we have a class discussion about the results and see if any group's prediction or hypotheses agreed with the results of the experiment. If not, we go back and determine if there is anything they could have done differently to obtain the results that they expected to see during the experiment.
MODELING AND PREDICTING DEMAND In Economics, a linear model is often used for the demand for a product as a function of its price. For instance, suppose Twin Pixie, a large supermarket chain, conducts a market analysis on its store brand of doughnut-shaped oat breakfast cereal. The chain sets various prices for its 15 oz. box at its different stores over a period of time. Then using this data, the Twin Pixie researchers project the weekly sales at the entire chain of stores for each price and obtain the data shown.
WEEKLY SALES DATA BASED ON MARKETING RESEARCH Price per box Boxes Sold $2.40 38,320 $2.60 33,710 $2.80 28,280 $3.00 26,550 $3.20 25,530 $3.40 22,170 $3.60 18,260
Using this data write a linear model for demand (in boxes sold per week) as a function of the price per box (in dollars). Describe the strength and direction of the linear correlation. Then use the model to predict weekly cereal sales if the price is dropped to $2.00 or raised to $4.00 per box.
Both are excellent examples. I believe that asking students to predict and support their predictions involve higher order thinking skills. Language Arts teachers typcially do a wonderful job of asking students to make predictions in regard to reading passages. These posted examples show that this instructional technique can easily be applied to all disciplines.
In the science classroom, generating and testing a hypotheses can be utilized easily. Before each experiment I have students make a prediction about the outcome of the experiment based on prior knowledge. They must provide an explanation of how or why they came up with their conclusion. After the lab we have a class discussion about the results and see if any group's prediction or hypotheses agreed with the results of the experiment. If not, we go back and determine if there is anything they could have done differently to obtain the results that they expected to see during the experiment.
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MODELING AND PREDICTING DEMAND
ReplyDeleteIn Economics, a linear model is often used for the demand for a product as a function of its price. For instance, suppose Twin Pixie, a large supermarket chain, conducts a market analysis on its store brand of doughnut-shaped oat breakfast cereal. The chain sets various prices for its 15 oz. box at its different stores over a period of time. Then using this data, the Twin Pixie researchers project the weekly sales at the entire chain of stores for each price and obtain the data shown.
WEEKLY SALES DATA BASED ON MARKETING RESEARCH
Price per box Boxes Sold
$2.40 38,320
$2.60 33,710
$2.80 28,280
$3.00 26,550
$3.20 25,530
$3.40 22,170
$3.60 18,260
Using this data write a linear model for demand (in boxes sold per week) as a function of the price per box (in dollars). Describe the strength and direction of the linear correlation. Then use the model to predict weekly cereal sales if the price is dropped to $2.00 or raised to $4.00 per box.
Both are excellent examples. I believe that asking students to predict and support their predictions involve higher order thinking skills. Language Arts teachers typcially do a wonderful job of asking students to make predictions in regard to reading passages. These posted examples show that this instructional technique can easily be applied to all disciplines.
ReplyDelete