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This week I’ve been interviewing guest experts for my upcoming Simple Self-Confidence Course, and I had the pleasure of meeting a truly amazing and beautiful woman, Karen Walrond. Karen hangs with the likes of Brene Brown and Oprah, but she is a down-to-earth, beautiful spirit whose mission is to celebrate something we all have in common — imperfection.

For my confidence course, Karen and I spoke a great deal about being different, having imperfections, and the impact these things have on our self-confidence. It is our imperfections that bind us to humanity and make us more approachable and connected with others. In the meantime, I would love to share Karen’s message with you in her 2012 TED talk in her hometown of Houston.

Karen has graciously offered to give away three signed hard copies of her beautiful book, The Beauty of Different: Observations of a Confident Misfit.

If you have any questions for Karen, she would be delighted to answer them in the comments as well!

If you want a checklist for self-publishing your bestseller then click here to check out our 46-point guide. I am a fan of viewing TED on line , but very often the impact of watching these presentations is like hearing a great sermon on Sunday, but by Tuesday, the key messages are forgotten because of the distractions of day to day life.

It’s funny how when we were young the worst thing that could happen to us was to stick out or somehow be different than those of our peers. I was diagnosed with Lichen Planus in 2009; an autoimmune condition which affects about 1 – 2% of the world’s population.

The rash was unsightly but it subsided and I was left with severe hyperpigmentation all over – worse still on my legs. I have since had another boyfriend and broken up with him; that break up did a double number on my confidence.

On the plus side, I try to be glad for the experience as I am aware of the things that are most important in life.

I firmly believe that the so-called imperfections in the physical body are simply a stereotype of society. I spent my life moving around – and I happen to be taller than most ladies and have bright red hair. By the way, Karen, I named the cliques at my school – they were either Friendlies or Unfriendlies. Barrie is a bestselling author with 10 books and counting, and teaches others how to publish and market their books at Authority Pub Academy. The general purpose of multiple regression (the term was first used by Pearson, 1908) is to learn more about the relationship between several independent or predictor variables and a dependent or criterion variable. Once this so-called regression line has been determined, the analyst can now easily construct a graph of the expected (predicted) salaries and the actual salaries of job incumbents in his or her company. In the social and natural sciences multiple regression procedures are very widely used in research.

See also Exploratory Data Analysis and Data Mining Techniques, the General Stepwise Regression topic, and the General Linear Models topic.

The general computational problem that needs to be solved in multiple regression analysis is to fit a straight line to a number of points. In the simplest case - one dependent and one independent variable - you can visualize this in a scatterplot. For example, the animation below shows a two dimensional regression equation plotted with three different confidence intervals (90%, 95% and 99%). In the multivariate case, when there is more than one independent variable, the regression line cannot be visualized in the two dimensional space, but can be computed just as easily.

Note that in this equation, the regression coefficients (or B coefficients) represent the independent contributions of each independent variable to the prediction of the dependent variable. The regression line expresses the best prediction of the dependent variable (Y), given the independent variables (X). R-Square, also known as the Coefficient of determination is a commonly used statistic to evaluate model fit.

Customarily, the degree to which two or more predictors (independent or X variables) are related to the dependent (Y) variable is expressed in the correlation coefficient R, which is the square root of R-square.

First of all, as is evident in the name multiple linear regression, it is assumed that the relationship between variables is linear.

The major conceptual limitation of all regression techniques is that you can only ascertain relationships, but never be sure about underlying causal mechanism.

Multiple regression is a seductive technique: "plug in" as many predictor variables as you can think of and usually at least a few of them will come out significant. The fitting of higher-order polynomials of an independent variable with a mean not equal to zero can create difficult multicollinearity problems. Even though most assumptions of multiple regression cannot be tested explicitly, gross violations can be detected and should be dealt with appropriately. How to find a critical value for a confidence levelHow to find a critical value for any confidence level (i.e. In celebration of Poetry month, students in English 8 created “found poems” by identifying an abstract word and then finding 6-10 words from a magazine. In fact, instead of allowing these imperfections to hold us back, they can actually be a source for building self-confidence. Tonight, when I am looking in the mirror, instead of looking for all the ways the flaws detract from the whole, I will instead try to see them as cracks, through which my light shines out. It’s definitely been a blow and a setback to my self confidence, as I struggle with my responses to everyday life, my identity and who I am post-trauma.

Having had chicken pox and knowing how fast my skin healed, I thought I would give it time. Maybe someday I will be brave enough to talk to my friends about it but I have a wall that is so high I cannot imagine climbing down from it totally.

It was really hard to stand out as the tall new girl while being a shy person, and it took me through my college years before I realized I had more to offer than just being the new strange thing.

She is a certified coach, and online teacher with several online courses on finding your passion, building confidence, and creating good habits. For example, a real estate agent might record for each listing the size of the house (in square feet), the number of bedrooms, the average income in the respective neighborhood according to census data, and a subjective rating of appeal of the house. Thus, the analyst is able to determine which position is underpaid (below the regression line) or overpaid (above the regression line), or paid equitably. These variables may, for example, represent IQ (intelligence as measured by a test) and school achievement (grade point average; GPA), respectively. The constant is also referred to as the intercept, and the slope as the regression coefficient or B coefficient. Another way to express this fact is to say that, for example, variable X1 is correlated with the Y variable, after controlling for all other independent variables. However, nature is rarely (if ever) perfectly predictable, and usually there is substantial variation of the observed points around the fitted regression line (as in the scatterplot shown earlier).

In practice this assumption can virtually never be confirmed; fortunately, multiple regression procedures are not greatly affected by minor deviations from this assumption. Again, even though most tests (specifically the F-test) are quite robust with regard to violations of this assumption, it is always a good idea, before drawing final conclusions, to review the distributions of the major variables of interest. For example, you would find a strong positive relationship (correlation) between the damage that a fire does and the number of firemen involved in fighting the blaze. Imagine that you have two predictors (X variables) of a person's height: (1) weight in pounds and (2) weight in ounces. Specifically, the polynomials will be highly correlated due to the mean of the primary independent variable. She believes, as I do, that our differences and our perceived imperfections are what make us unique, authentic, and interesting. If we could get everyone to view the world this way, we truly could change the societal definition of beauty. The good part is, I’m often able to identify and connect with others like me, almost like a sixth sense. Nothing warms my heart more than encountering someone who has experienced teh negatives of perceived imperfections – it’s a kindred spirit thing that is very rare to find. But I’m in my late 20s now and see the gifts that all those moves have bestowed on me. Once this information has been compiled for various houses it would be interesting to see whether and how these measures relate to the price for which a house is sold. For example, educational researchers might want to learn what are the best predictors of success in high-school.

Each point in the plot represents one student, that is, the respective student's IQ and GPA. This type of correlation is also referred to as a partial correlation (this term was first used by Yule, 1907). The deviation of a particular point from the regression line (its predicted value) is called the residual value. When the variability of the residual values around the regression line relative to the overall variability is small, the predictions from the regression equation are good. To interpret the direction of the relationship between variables, look at the signs (plus or minus) of the regression or B coefficients. However, as a rule it is prudent to always look at bivariate scatterplot of the variables of interest. You can produce histograms for the residuals as well as normal probability plots, in order to inspect the distribution of the residual values.

This problem is compounded when, in addition, the number of observations is relatively low.

Obviously, our two predictors are completely redundant; weight is one and the same variable, regardless of whether it is measured in pounds or ounces.

Often, excluding just a single extreme case can yield a completely different set of results. Stutzman"If you ever go to gouge someone's eyes out, make sure you grab from near the nose.

The skills needed for good leadership are present in all of us, but not all of us are natural leaders. So far I have smashed 4 mirrors in anger at my reflection, broken up with a man who still adores me because I didn’t want to deprive him of someone normal :S (though other reasons played ) and in the early stage of the condition, had someone refuse to hug me.

I recently met this woman at the gym with obvious psoriasis plaques and I thought it was kick-ass that she didn’t care. I do my best to share them, and I’m grateful that something good has come out of my years of painful awkwardness. Psychologists may want to determine which personality variable best predicts social adjustment. For example, if there is no relationship between the X and Y variables, then the ratio of the residual variability of the Y variable to the original variance is equal to 1.0.

If curvature in the relationships is evident, you may consider either transforming the variables, or explicitly allowing for nonlinear components.

Intuitively, it is clear that you can hardly draw conclusions from an analysis of 100 questionnaire items based on 10 respondents. Our ALPs series is designed to identify, embrace and and strengthen our ALPs participants leadership abilities.

I have also lost count of the number of times I have cried myself to sleep because I look . A great job, an amazing personality (I work very hard at being the best person I can be) a family, friends etc. Sociologists may want to find out which of the multiple social indicators best predict whether or not a new immigrant group will adapt and be absorbed into society. Specifically, the program will compute a line so that the squared deviations of the observed points from that line are minimized. At first this may seem odd; however, if we were to add the variable Gender into the multiple regression equation, this correlation would probably disappear.

Of course, if the B coefficient is equal to 0 then there is no relationship between the variables. Even though this example is fairly obvious, in real correlation research, alternative causal explanations are often not considered.

When there are very many variables involved, it is often not immediately apparent that this problem exists, and it may only manifest itself after several variables have already been entered into the regression equation. See, for example, the classic text by Neter, Wasserman, & Kutner (1985, Chapter 9), for a detailed discussion of this issue (and analyses with polynomial models in general).

I work out and have a great body to show for it (or in this case, to not show – I am ever so grateful for opaque tights). This is because women, on the average, have longer hair than men; they also are shorter on the average than men.

If X and Y are perfectly related then there is no residual variance and the ratio of variance would be 0.0, making R-square = 1. Nevertheless, when this problem occurs it means that at least one of the predictor variables is (practically) completely redundant with other predictors.

How to find a critical value z.05 in the Standard Normal N(0,1) a€¦What is a Confidence Interval? Thus, after we remove this gender difference by entering Gender into the equation, the relationship between hair length and height disappears because hair length does not make any unique contribution to the prediction of height, above and beyond what it shares in the prediction with variable Gender.

Some days it is a struggle and I have to remind myself that it is alright to have bad days.

Put another way, after controlling for the variable Gender, the partial correlation between hair length and height is zero. The biologic industry, including .How to Identify the Notation for the Mean and Variance of a Discrete Random VariableUse the confidence level and sample data to find a confidence interval for estimating the population mu. I have started flirting with this guy I like which is a step on its own; though despite obvious signs he likes I retreat slightly because I don’t think I could handle it if he rejected me because of my skin. TMO Adventures provide an opportunity to realize a group's governing principles, values, ethics and practice core competencies in a safe and supportive environment. Our challenges are experiential in nature and we encourage continued teamwork, realistic goal setting, honest feedback and shared learning in a experiential process which stimulates our creative thinking and problem solving skill sets.

Groups tend to develop a sense of community that wants to be successful at what they are engaged in. Many of these I had come across before but the one that stood out for a€¦ClassZone Book Finder. Participants find a new sense of confidence in themselves an understanding A and appreciation for others that transfers over to the school and their community. We believe that together, the teachers and students will return to their classrooms and will ultimately be linked together through their shared experience to achieve the common goal of linking adventure through education. A 10:00 am - 2:00 pmHave you ever wondered if you could you make it on your own in the woods? You are the best thing you have."During this four-hour program you will use critical thinking skills and a positive attitude to complete this 'Survival' scenario. You will learn impromptu wilderness medical skills (First-Aid without a kit), look for natural shelter, build a debris shelter, find safe drinking water, find resources for making primitive tools, make a primitive weapon, track wildlife, build a fire, learn back country cooking skills and what leave no trace ethics are, even forecast the weather! All participants acquire real skills and an increased awareness of themselves and their environment. They also develop a more positive self-image through an authentic sense of personal accomplishment. All students should read or listen to the book Hatchet by Gary Paulsen and come with small blank page journal and a pen. Learn the skills that will save your life and or your family or friends.This is a course that you won't want to missDress casual and warm. Learn outdoor survival skills plus how to build a matchless fireBring water - snack & lunch, ID books, magnifying glass if you have them. All programs require proper clothing and rain gear, sturdy footwear, sunscreen, water bottle. TMO Adventures provide an opportunity to realize a group's governing principles, values, ethics and practice core competencies in a safe and supportive environment. Just click to add your own content.You can use this page for anything you like, but we recommend focusing on one or two related topics to avoid confusing your readers.

For my confidence course, Karen and I spoke a great deal about being different, having imperfections, and the impact these things have on our self-confidence. It is our imperfections that bind us to humanity and make us more approachable and connected with others. In the meantime, I would love to share Karen’s message with you in her 2012 TED talk in her hometown of Houston.

Karen has graciously offered to give away three signed hard copies of her beautiful book, The Beauty of Different: Observations of a Confident Misfit.

If you have any questions for Karen, she would be delighted to answer them in the comments as well!

If you want a checklist for self-publishing your bestseller then click here to check out our 46-point guide. I am a fan of viewing TED on line , but very often the impact of watching these presentations is like hearing a great sermon on Sunday, but by Tuesday, the key messages are forgotten because of the distractions of day to day life.

It’s funny how when we were young the worst thing that could happen to us was to stick out or somehow be different than those of our peers. I was diagnosed with Lichen Planus in 2009; an autoimmune condition which affects about 1 – 2% of the world’s population.

The rash was unsightly but it subsided and I was left with severe hyperpigmentation all over – worse still on my legs. I have since had another boyfriend and broken up with him; that break up did a double number on my confidence.

On the plus side, I try to be glad for the experience as I am aware of the things that are most important in life.

I firmly believe that the so-called imperfections in the physical body are simply a stereotype of society. I spent my life moving around – and I happen to be taller than most ladies and have bright red hair. By the way, Karen, I named the cliques at my school – they were either Friendlies or Unfriendlies. Barrie is a bestselling author with 10 books and counting, and teaches others how to publish and market their books at Authority Pub Academy. The general purpose of multiple regression (the term was first used by Pearson, 1908) is to learn more about the relationship between several independent or predictor variables and a dependent or criterion variable. Once this so-called regression line has been determined, the analyst can now easily construct a graph of the expected (predicted) salaries and the actual salaries of job incumbents in his or her company. In the social and natural sciences multiple regression procedures are very widely used in research.

See also Exploratory Data Analysis and Data Mining Techniques, the General Stepwise Regression topic, and the General Linear Models topic.

The general computational problem that needs to be solved in multiple regression analysis is to fit a straight line to a number of points. In the simplest case - one dependent and one independent variable - you can visualize this in a scatterplot. For example, the animation below shows a two dimensional regression equation plotted with three different confidence intervals (90%, 95% and 99%). In the multivariate case, when there is more than one independent variable, the regression line cannot be visualized in the two dimensional space, but can be computed just as easily.

Note that in this equation, the regression coefficients (or B coefficients) represent the independent contributions of each independent variable to the prediction of the dependent variable. The regression line expresses the best prediction of the dependent variable (Y), given the independent variables (X). R-Square, also known as the Coefficient of determination is a commonly used statistic to evaluate model fit.

Customarily, the degree to which two or more predictors (independent or X variables) are related to the dependent (Y) variable is expressed in the correlation coefficient R, which is the square root of R-square.

First of all, as is evident in the name multiple linear regression, it is assumed that the relationship between variables is linear.

The major conceptual limitation of all regression techniques is that you can only ascertain relationships, but never be sure about underlying causal mechanism.

Multiple regression is a seductive technique: "plug in" as many predictor variables as you can think of and usually at least a few of them will come out significant. The fitting of higher-order polynomials of an independent variable with a mean not equal to zero can create difficult multicollinearity problems. Even though most assumptions of multiple regression cannot be tested explicitly, gross violations can be detected and should be dealt with appropriately. How to find a critical value for a confidence levelHow to find a critical value for any confidence level (i.e. In celebration of Poetry month, students in English 8 created “found poems” by identifying an abstract word and then finding 6-10 words from a magazine. In fact, instead of allowing these imperfections to hold us back, they can actually be a source for building self-confidence. Tonight, when I am looking in the mirror, instead of looking for all the ways the flaws detract from the whole, I will instead try to see them as cracks, through which my light shines out. It’s definitely been a blow and a setback to my self confidence, as I struggle with my responses to everyday life, my identity and who I am post-trauma.

Having had chicken pox and knowing how fast my skin healed, I thought I would give it time. Maybe someday I will be brave enough to talk to my friends about it but I have a wall that is so high I cannot imagine climbing down from it totally.

It was really hard to stand out as the tall new girl while being a shy person, and it took me through my college years before I realized I had more to offer than just being the new strange thing.

She is a certified coach, and online teacher with several online courses on finding your passion, building confidence, and creating good habits. For example, a real estate agent might record for each listing the size of the house (in square feet), the number of bedrooms, the average income in the respective neighborhood according to census data, and a subjective rating of appeal of the house. Thus, the analyst is able to determine which position is underpaid (below the regression line) or overpaid (above the regression line), or paid equitably. These variables may, for example, represent IQ (intelligence as measured by a test) and school achievement (grade point average; GPA), respectively. The constant is also referred to as the intercept, and the slope as the regression coefficient or B coefficient. Another way to express this fact is to say that, for example, variable X1 is correlated with the Y variable, after controlling for all other independent variables. However, nature is rarely (if ever) perfectly predictable, and usually there is substantial variation of the observed points around the fitted regression line (as in the scatterplot shown earlier).

In practice this assumption can virtually never be confirmed; fortunately, multiple regression procedures are not greatly affected by minor deviations from this assumption. Again, even though most tests (specifically the F-test) are quite robust with regard to violations of this assumption, it is always a good idea, before drawing final conclusions, to review the distributions of the major variables of interest. For example, you would find a strong positive relationship (correlation) between the damage that a fire does and the number of firemen involved in fighting the blaze. Imagine that you have two predictors (X variables) of a person's height: (1) weight in pounds and (2) weight in ounces. Specifically, the polynomials will be highly correlated due to the mean of the primary independent variable. She believes, as I do, that our differences and our perceived imperfections are what make us unique, authentic, and interesting. If we could get everyone to view the world this way, we truly could change the societal definition of beauty. The good part is, I’m often able to identify and connect with others like me, almost like a sixth sense. Nothing warms my heart more than encountering someone who has experienced teh negatives of perceived imperfections – it’s a kindred spirit thing that is very rare to find. But I’m in my late 20s now and see the gifts that all those moves have bestowed on me. Once this information has been compiled for various houses it would be interesting to see whether and how these measures relate to the price for which a house is sold. For example, educational researchers might want to learn what are the best predictors of success in high-school.

Each point in the plot represents one student, that is, the respective student's IQ and GPA. This type of correlation is also referred to as a partial correlation (this term was first used by Yule, 1907). The deviation of a particular point from the regression line (its predicted value) is called the residual value. When the variability of the residual values around the regression line relative to the overall variability is small, the predictions from the regression equation are good. To interpret the direction of the relationship between variables, look at the signs (plus or minus) of the regression or B coefficients. However, as a rule it is prudent to always look at bivariate scatterplot of the variables of interest. You can produce histograms for the residuals as well as normal probability plots, in order to inspect the distribution of the residual values.

This problem is compounded when, in addition, the number of observations is relatively low.

Obviously, our two predictors are completely redundant; weight is one and the same variable, regardless of whether it is measured in pounds or ounces.

Often, excluding just a single extreme case can yield a completely different set of results. Stutzman"If you ever go to gouge someone's eyes out, make sure you grab from near the nose.

The skills needed for good leadership are present in all of us, but not all of us are natural leaders. So far I have smashed 4 mirrors in anger at my reflection, broken up with a man who still adores me because I didn’t want to deprive him of someone normal :S (though other reasons played ) and in the early stage of the condition, had someone refuse to hug me.

I recently met this woman at the gym with obvious psoriasis plaques and I thought it was kick-ass that she didn’t care. I do my best to share them, and I’m grateful that something good has come out of my years of painful awkwardness. Psychologists may want to determine which personality variable best predicts social adjustment. For example, if there is no relationship between the X and Y variables, then the ratio of the residual variability of the Y variable to the original variance is equal to 1.0.

If curvature in the relationships is evident, you may consider either transforming the variables, or explicitly allowing for nonlinear components.

Intuitively, it is clear that you can hardly draw conclusions from an analysis of 100 questionnaire items based on 10 respondents. Our ALPs series is designed to identify, embrace and and strengthen our ALPs participants leadership abilities.

I have also lost count of the number of times I have cried myself to sleep because I look . A great job, an amazing personality (I work very hard at being the best person I can be) a family, friends etc. Sociologists may want to find out which of the multiple social indicators best predict whether or not a new immigrant group will adapt and be absorbed into society. Specifically, the program will compute a line so that the squared deviations of the observed points from that line are minimized. At first this may seem odd; however, if we were to add the variable Gender into the multiple regression equation, this correlation would probably disappear.

Of course, if the B coefficient is equal to 0 then there is no relationship between the variables. Even though this example is fairly obvious, in real correlation research, alternative causal explanations are often not considered.

When there are very many variables involved, it is often not immediately apparent that this problem exists, and it may only manifest itself after several variables have already been entered into the regression equation. See, for example, the classic text by Neter, Wasserman, & Kutner (1985, Chapter 9), for a detailed discussion of this issue (and analyses with polynomial models in general).

I work out and have a great body to show for it (or in this case, to not show – I am ever so grateful for opaque tights). This is because women, on the average, have longer hair than men; they also are shorter on the average than men.

If X and Y are perfectly related then there is no residual variance and the ratio of variance would be 0.0, making R-square = 1. Nevertheless, when this problem occurs it means that at least one of the predictor variables is (practically) completely redundant with other predictors.

How to find a critical value z.05 in the Standard Normal N(0,1) a€¦What is a Confidence Interval? Thus, after we remove this gender difference by entering Gender into the equation, the relationship between hair length and height disappears because hair length does not make any unique contribution to the prediction of height, above and beyond what it shares in the prediction with variable Gender.

Some days it is a struggle and I have to remind myself that it is alright to have bad days.

Put another way, after controlling for the variable Gender, the partial correlation between hair length and height is zero. The biologic industry, including .How to Identify the Notation for the Mean and Variance of a Discrete Random VariableUse the confidence level and sample data to find a confidence interval for estimating the population mu. I have started flirting with this guy I like which is a step on its own; though despite obvious signs he likes I retreat slightly because I don’t think I could handle it if he rejected me because of my skin. TMO Adventures provide an opportunity to realize a group's governing principles, values, ethics and practice core competencies in a safe and supportive environment. Our challenges are experiential in nature and we encourage continued teamwork, realistic goal setting, honest feedback and shared learning in a experiential process which stimulates our creative thinking and problem solving skill sets.

Groups tend to develop a sense of community that wants to be successful at what they are engaged in. Many of these I had come across before but the one that stood out for a€¦ClassZone Book Finder. Participants find a new sense of confidence in themselves an understanding A and appreciation for others that transfers over to the school and their community. We believe that together, the teachers and students will return to their classrooms and will ultimately be linked together through their shared experience to achieve the common goal of linking adventure through education. A 10:00 am - 2:00 pmHave you ever wondered if you could you make it on your own in the woods? You are the best thing you have."During this four-hour program you will use critical thinking skills and a positive attitude to complete this 'Survival' scenario. You will learn impromptu wilderness medical skills (First-Aid without a kit), look for natural shelter, build a debris shelter, find safe drinking water, find resources for making primitive tools, make a primitive weapon, track wildlife, build a fire, learn back country cooking skills and what leave no trace ethics are, even forecast the weather! All participants acquire real skills and an increased awareness of themselves and their environment. They also develop a more positive self-image through an authentic sense of personal accomplishment. All students should read or listen to the book Hatchet by Gary Paulsen and come with small blank page journal and a pen. Learn the skills that will save your life and or your family or friends.This is a course that you won't want to missDress casual and warm. Learn outdoor survival skills plus how to build a matchless fireBring water - snack & lunch, ID books, magnifying glass if you have them. All programs require proper clothing and rain gear, sturdy footwear, sunscreen, water bottle. TMO Adventures provide an opportunity to realize a group's governing principles, values, ethics and practice core competencies in a safe and supportive environment. Just click to add your own content.You can use this page for anything you like, but we recommend focusing on one or two related topics to avoid confusing your readers.

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10.08.2014 at 13:59:14 Spirit retreat organization (non-religious and non-denominational) guiding.

10.08.2014 at 10:16:59 Snack with kids, tell them soon as again and patiently wend.