Comparing Hardness and Density of a Sol
Comparing Hardness and Density of a Solid
Name of Solid
Hardness
Density Talc 1 2.75 Fluorite 4 3.13 Calcite 3 2.71 Quartz 7 2.62 Gypsum 2 2.3 Apatite 5 3.19
My graph has no correlation.
My hypothesis for this Experiment is that a mineral is able to scratch a mineral with a lower number and can, therefore be scratched by a mineral with a higher number. A mineral's density is the amount of matter in a given space (mass/volume). Each mineral has a characteristic density (density does not vary with the size of the mineral). I found out that A fngernail will scratch Talc and Gypsum, A penny will scratch Calcite and Fluorite, A file will scratch Quartz, and Glass, Knife blade, or Nail wll scratch Apatite.
Two variables that covary are said to be related, but not all variables that covary represent a causal relationship. You can describe the relationship between two variables in terms of direction (positive or negative), form (general, linear, nonlinear, or monotonic), and strength.
One of the best places to start when assessing relationships is looking at a graph like a scatter plot or a matrix plot that can graphically reveal the direction, form, and strength of a relationship.
Name of Solid
Hardness
Density Talc 1 2.75 Fluorite 4 3.13 Calcite 3 2.71 Quartz 7 2.62 Gypsum 2 2.3 Apatite 5 3.19
My graph has no correlation.
My hypothesis for this Experiment is that a mineral is able to scratch a mineral with a lower number and can, therefore be scratched by a mineral with a higher number. A mineral's density is the amount of matter in a given space (mass/volume). Each mineral has a characteristic density (density does not vary with the size of the mineral). I found out that A fngernail will scratch Talc and Gypsum, A penny will scratch Calcite and Fluorite, A file will scratch Quartz, and Glass, Knife blade, or Nail wll scratch Apatite.
Two variables that covary are said to be related, but not all variables that covary represent a causal relationship. You can describe the relationship between two variables in terms of direction (positive or negative), form (general, linear, nonlinear, or monotonic), and strength.
One of the best places to start when assessing relationships is looking at a graph like a scatter plot or a matrix plot that can graphically reveal the direction, form, and strength of a relationship.